Our Work
Here is where you can find some of the toolkits that I have developed
01
Fusion X
The toolkit is a desktop-based data ingestion and preprocessing interface designed for multi-modal remote sensing workflows. It guides users through uploading LiDAR, hyperspectral imagery, and elevation data, confirms successful loading, and organizes inputs into a consistent structure for model training, classification, or mapping tasks.
02
HSIDEM Toolkit
HSIDEM Toolkit is a specialized fusion framework that integrates Hyperspectral Imagery (HSI) with Digital Elevation Models (DEM) and thermal imagery to improve spatial-spectral analysis in remote sensing applications. By combining detailed spectral signatures from HSI with terrain and elevation data from DEM, the toolkit enables improved feature discrimination, material classification, and topographic context extraction. HSIDEM is particularly useful in environmental monitoring, geology, forestry, and precision agriculture, where both spectral richness and elevation play critical roles in interpretation and decision-making.
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03
Pointcloud-DEM Toolkit
PClDEM Toolkit is a specialized software suite designed to transform 3D point cloud datasets obtained from LiDAR, photogrammetry, or drone surveys into high-resolution Digital Elevation Models (DEMs) and thermal imagery. Leveraging advanced filtering, ground-point extraction, and interpolation algorithms, PClDEM automatically distinguishes terrain from non-ground features like vegetation or structures. It then generates precise elevation grids that can be used for a variety of geospatial applications, including hydrological modeling, topographic mapping, infrastructure planning, and volumetric analysis. The toolkit is engineered for efficiency and accuracy, providing GIS professionals and researchers with an end-to-end solution for converting unstructured point clouds into readily usable terrain surfaces.
04
Banding Toolkit
developed a Python tool to mitigate banding issues within LiDAR data. This tool effectively addresses the issues associated with uneven point density, intensity, and elevation values in the data. By working on this project, I not only honed my Python programming skills but also gained practical experience in remote sensing and data processing. My tool enhances the accuracy and reliability of LiDAR data, which is crucial for a wide range of applications, such as topographic mapping, environmental analysis, and infrastructure assessment. The tool was eventually incorporated into their proprietary LiDAR data processing software called LMS Pro
