papers

Publications (7)

cs.DS2015

An Efficient Assignment of Drainage Direction Over Flat Surfaces in Raster Digital Elevation Models

Richard Barnes, Clarence Lehman, David Mulla

In processing raster digital elevation models (DEMs) it is often necessary to assign drainage directions over flats---that is, over regions with no local elevation gradient. This p…

cs.CV2026

UAV3DCrop: Benchmarking 3D Reconstruction in Repeated Multi-Angle UAV Crop Surveys

Junxiong Zhou, Xuechen Li, Chonghao Qiu +11

Accurate 3D crop monitoring underpins data-driven precision agriculture by enabling field-scale analysis of plant structure, growth dynamics, and management response. Modern 3D rec…

cs.LG2025

Towards Fine-Tuning-Based Site Calibration for Knowledge-Guided Machine Learning: A Summary of Results

Ruolei Zeng, Arun Sharma, Shuai An +5

Accurate and cost-effective quantification of the agroecosystem carbon cycle at decision-relevant scales is essential for climate mitigation and sustainable agriculture. However, b…

cs.DC2016

Distributed Parallel D8 Up-Slope Area Calculation in Digital Elevation Models

Richard Barnes, Clarence Lehman, David Mulla

This paper presents a parallel algorithm for calculating the eight-directional (D8) up-slope contributing area in digital elevation models (DEMs). In contrast with previous algorit…

cs.CV2024

Combining Satellite and Weather Data for Crop Type Mapping: An Inverse Modelling Approach

Praveen Ravirathinam, Rahul Ghosh, Ankush Khandelwal +3

Accurate and timely crop mapping is essential for yield estimation, insurance claims, and conservation efforts. Over the years, many successful machine learning models for crop map…

cs.CV2021

CalCROP21: A Georeferenced multi-spectral dataset of Satellite Imagery and Crop Labels

Rahul Ghosh, Praveen Ravirathinam, Xiaowei Jia +3

Mapping and monitoring crops is a key step towards sustainable intensification of agriculture and addressing global food security. A dataset like ImageNet that revolutionized compu…