Geo-Sensing

\textit{1) Hyrank dataset:}

The dataset was developed with the support of the ISPRS Scientific Committee, taken by the Hyerion sensor carried by NASA's EO-1 satellite. After screening 242 spectral bands from SWIR and VNIR sensors, 176 spectral bands were exported. The total of 5 images and 14 land-cover categories were provided. The Dioni image size is $250 \times1376 $, and the Loukia image size is $249 \times945 $, both with a spatial resolution of 30m. Two scene images are shown in Fig. \ref{Hyrank}.

\textit{2) Houston dataset:}

The dataset used in this study combines remote sensing data from multiple advanced platforms, including Synthetic Aperture Radar (SAR) from Sentinel-1, multispectral imagery from Sentinel-2, and LiDAR measurements from the Global Ecosystem Dynamics Investigation (GEDI) mission. Each of these sources offers unique and complementary information, enabling a detailed and comprehensive analysis of forest canopy height across diverse and ecologically significant regions in northern Vietnam.

Decentralized Collaborative Simultaneous Localization and Mapping (C-SLAM) is essential to enable multi-robot missions in unknown environments without relying on pre-existing localization and communication infrastructure. This technology is anticipated to play a key role in the exploration of the Moon, Mars, and other planets. In this work, we introduce a novel dataset collected during C-SLAM experiments involving three robots operating on a Mars analogue terrain.

This dataset is from "One-Stage Cascade Refinement Networks for Infrared Small Target Detection." It includes 427 infrared images and 480 targets (due to the lack of infrared sequences, SIRST also contains infrared images at a wavelength of 950 nm, in addition to shortwave and midwave infrared images). Approximately 90% of the images contain only one target, while about 10% have multiple targets (which may be overlooked in sparse/significant methods due to global unique assumptions).