For collecting data of Kshetrapal landslide area, Chamoli-District, Uttarakhand, India, TLS and UAV was used ( Figure 16 ). TLS is a type of remote detecting that employs lasers to gather 3D spatial data from environmental study targets.

TLS has strong penetration in vegetated areas, high accuracy, and strong stability. UAV mapping creates 2D aerial data and produces 3D clouds of point photos as opposed to TLS. Its field of vision is less constrained by the terrain; thus, it can gather more topographical data in a shorter amount of time. Aerial triangulation, a technique for tying point densification that makes use of the inherent geometric properties of aerial photogrammetry, produces the 3D clouds of points of UAV mapping. A local organization model (optical or computerized) that corresponds to the arena is built using overlapped aerial photos and photogrammetric techniques, and densified point cloud sets are given planar coordinates and elevations using this method. UAV aerial photography typically has better accuracy and resolution than TLS.

1) Mission Planning:

2) Data Capture:

3) PPK Data Processing and Geotagging:

4) Data Processing and Product Generation:

1) Target Placement:

2) TLS Stationing:

3) Data Acquisition:

4) Data Collection:

The observational evidence shows that UAV technology can be used to exhibit a comprehensive surveillance strategy in ground measuring engaged in collapse. The current study’s surface observation method and data image analysis flowchart are shown in Figure 17 . Photogrammetric programs are used to collect research site data and analyze images. Data analysis begins after data collection. The 3D model was georeferenced utilizing determined control points after processing the data. DEM would be developed here.

A High-resolution Digital Elevation Model (CartoDEM) was created by the Indian Space Research Organization (ISRO) with data from the Cartosat-1 satellite. Among the many uses for CartoDEM’s precise surface elevation data are topographic mapping, city planning, infrastructure construction, watershed management, and catastrophe prevention and mitigation. With a spatial resolution of around 30 meters, it is well-suited for mapping and analyzing large-scale areas. For initiatives in India’s public and commercial sectors that need accurate terrain data, CartoDEM is a must-have geospatial analytic tool. Figure 18(a) (Source: https://www.isro.gov.in/Cartosat_1_Completes_a_Decade_in_orbit.html )

NASA’s Terra Satellite’s Advanced Space Borne Thermal Emission and Reflection Radiometer (ASTER) sensor acquired worldwide elevation data to create the ASTER Digital Elevation Model (DEM). ASTER DEM, launched in 1999, offers 30-meter elevation data for most of Earth between latitudes 83˚N and 83˚S. This DEM is utilized in topographic mapping, climate modeling, land-use planning, and natural hazard assessment. High-resolution elevation data permits extensive topography study, making it useful for academics and planners worldwide. Figure 18(b) (Source: https://asterweb.jpl.nasa.gov/gdem.asp )

NASA and the National Geospatial-Intelligence Agency (NGA) developed the Shuttle Radar Topography Mission (SRTM) Digital Elevation Model (DEM) in 2000, which provides comprehensive elevation information on a worldwide scale. SRTM used radar interferometry to collect elevation data with almost worldwide coverage between latitudes 60˚N and 56˚S, with a resolution of 30 meters in the United States and 90 meters in the majority of other areas. This DEM is widely used in hydrology, geology, environmental management, and urban planning. It aids in terrain analysis, flood modeling, and infrastructure development by providing accessible and reliable elevation data for a broad range of applications throughout the globe. Figure 18(c) (Source: https://www.earthdata.nasa.gov/sensors/srtm )

The Advanced Land Observing Satellite (ALOS) 3D, commonly known as ALOS World 3D (AW3D), is a high-resolution global digital elevation model (DEM) created from data collected by the Panchromatic Remote-sensing Instrument for Stereo Mapping (PRISM) aboard Japan’s ALOS satellite. The ALOS 3D DEM has a spatial resolution of up to 5 meters, making it one of the most precise global elevation models currently accessible. It covers the whole terrestrial area of the Earth and is used in a variety of applications such as disaster management, urban planning, infrastructure construction, and environmental monitoring. Its great precision and rich detail make it an indispensable tool for detailed terrain research and geospatial investigations. Figure 18(d) (Source: https://earth.esa.int/eogateway/missions/alos )

TanDEM is Designed by the German Aerospace Center (DLR) in collaboration with Airbus Defence and Space, TanDEM is a digital elevation model (DEM). Two very similar satellites, TerraSAR and TanDEM, flying in close formation to provide an extremely precise, worldwide DEM, comprised this project. With vertical accuracy between 1 and 2 meters, the TanDEM DEM offers elevation data at a 12-meter spatial resolution. Widely utilized for purposes in topographic mapping, hydrology, forestry, infrastructure development, and disaster management, it covers the whole terrestrial surface of the Earth. For thorough terrain study and many scientific and commercial tasks, the exact elevation data from TanDEM is indispensable. Figure 18(e) (Source: https://gdk.gdi-de.org/geonetwork/srv/api/records/5eecdf4c-de57-4624-99e9-60086b032aea ).

MERIT DEM, which stands for “Multi-Error-Removed Improved-Terrain DEM,” is a global digital elevation model that makes earlier DEM datasets, like SRTM and ASTER, more accurate by getting rid of many of the mistakes they had. MERIT DEM was created by experts at the University of Tokyo and other schools working together. It fixes mistakes such as absolute bias, stripe noise, tree height bias, and more. It gives a good elevation model with a precision of about 3 seconds, which is about 90 meters at the equator. This makes it useful for water modeling, figuring out the risk of flooding, and other earth science tasks. The best thing about MERIT DEM is that it is more accurate and consistent, which makes it easier to do more accurate and in-depth analyses in many geospatial studies. Figure 18(f) (Source: http://hydro.iis.u-tokyo.ac.jp/~yamadai/MERIT_DEM/ )

Forest and Buildings Gone Copernicus DEM is a modified DEM. FABDEM removes forest canopies and structures from regular DEMs to better portray the naked soil. Hydrological modeling, flood risk assessment, and infrastructure design benefit from an unobstructed perspective of the terrain. FABDEM uses vegetation and structural correction methods to provide a dataset that better depicts land topography. Figure 18(g) (Source: https://gee-community-catalog.org/projects/fabde )

White Box Tool (WBT) is plugging-in software specifically designed to study geographical data. It includes a comprehensive collection of more than 550 tools designed for the manipulation and analysis of various forms of geographical data. One of its notable attributes is its wide utilization of parallel computing, eliminating the requirement for additional libraries like GDAL. The white box approach utilizes prior knowledge of geometry to formulate its model.

The WBT enables detailed morphometric evaluation of terrain features that are important for studying landslides in the Chamoli district of the Himalayas. By utilizing high-resolution DEMs obtained from UAV or TLS data, researchers are able to calculate important factors such as slope angle, topographic indices and aspect using the following mathematical formulas:

Slope degree = $\text{arctan}\left(\sqrt{{\left(\frac{\partial w}{\partial u}\right)}^2+{\left(\frac{\partial w}{\partial v}\right)}^2}\right)$ (1)

The symbols $\frac{\partial w}{\partial u}$ and $\frac{\partial w}{\partial v}$ represent the fractional derivatives of the elevation w with respect to the variables u and v, accordingly.

Aspect (degree) = $\text{arctan}2\left(-\frac{\partial w}{\partial v},-\frac{\partial w}{\partial u}\right)$ +360˚ (if less than 0) (2)

The arctan2 function is a mathematical function that calculates an angle from the coordinates u and v of the Cartesian plane.

Topographic Wetness Index (TWI) = $\ln \left(\frac{A}{\text{tan}\left(\beta \right)}\right)$ (3)

where A is the local upslope contributing area and $\beta$ is the local slope gradient in radians.

Compound Topographic Index (CTI) = $\ln \left(\frac{A}{\text{tan}\left(\beta \right)}\right)\times S$, where S is the slope. (4)

These formulas illustrate how Whitebox Tool utilizes mathematical expressions to compute various morphometric parameters essential for terrain analysis and modeling. The software automates these calculations based on input DEM data, providing researchers with quantitative insights into landscape characteristics and processes. These metrics provide insights into terrain stability and susceptibility to landslides. White box method interprets the DEM geometry directly into UAV parameters using a compilation of formulae software such as DATCOM, AVL or TORNADO. By leveraging advanced geospatial techniques, this software supports informed decision-making for disaster risk reduction and land management strategies in Chamoli and similar Himalayan environments. In the context of landslide research, White Box Tool serves as a versatile toolset for morphometric analysis, offering capabilities to derive detailed terrain parameters essential for assessing landslide risk factors and identifying vulnerable areas.