Semantic image Segmentation to achieve building footprints of the old cluster area of Nepal like Bhaktapur Municipality, Thimi , and etc.

Above ground biomass estimation using Random Forest Regression in Google Earth Engine

Spectral indices are combinations of spectral reflectance from two or more wavelengths that indicate the relative abundance of features of interest.

This is a plugin to load OSM and satellite imagery in QGIS. All code related to this plugin is freely available on GitHub.

Change Detection of Kathmandu Valley using different Machine Learning classifiers like Random Forest (RF), Support Vector Machine(SVM) and Classification and Regression Tree (CART).

Geospatial Analysis on the to explore spatial patterns, relationships, and trends on districtwise dengue cases, population, population density, average temperature, and precipitation,

Semantic image segmentation to extract the road from the high resolution satellite imagery.

This is a QGIS plugin to segment building polygon from the images provided.

This is a tool for closed traverse with two known coordinates, included angle and distance between the station.

This is a tool to extract building footprints using instance segmentation.

HPP is a surveying method used to measure the exact location of the hidden survey point when there is obstructions like trees, walls, or buildings. It is also mainly used to measure the elevation of the sewer inlet and outlet pipe where the target cannot be held straight.

Spectral index for detecting urban and built up areas based on the red and blue bands.

Calculate the distance between two points along the route by querying the name of the route.

Automative map production and managing map layouts programmatically.

XML-based open standard to represent 3D city models.

Bhaktapur Buildings Dataset consists of 10000 aerial images of the Bhaktapur area, with each of the images being 300x300 pixels for an area of 800 square meters.

ResNet is a deep convolutional neural network used in computer vision which addresses the vanishing gradient problems.

You Only Look Once (YOLO)