To tackle the data sparsity issue of aerial images on inland waterway fluvial scenes, we collected this image dataset for semantic segmentation neural networks. Images have been manually selected and semantically labeled with emphasis on extruded obstacles from river and riverbank, to form the novel dataset with 8 classes (Water, Boat, Bridge, Sky, Forest vegetation, Dry sediment, Drone itself and in-river Obstacles) and 816 high-resolution (2K and 2.7K) images in total. 

The images were collected during fall of 2021 on segments of Wabash River and Wildcat Creek in Indiana, USA. More specifically, Wabash River data was collected along the river segment to the east of Prophetstown State Park (3.65km), as well as its upper stream at intersection of Wabash River and Americus Road, and Wildcat Creek data was collected from Wildcat Creek Park to Peters Mill Access (4.71km), at Mis-So-Lah Public Access Point, as well as intersections of Wildcat Creek with Schuyler Avenue and East 100 North Road.

The unzipped AerialFluvialDataset.zip file contains 2 zipped subset files: WabashRiverDataset.zip and WildcatCreekDataset.zip. After unzipped these 2 files, the overall directory structure is as follows:
•	AerialFluvialDataset
•	WabashRiverDataset
•	wabash_dataset
•	bridge1_dataset
•	WildcatCreekDataset
•	wildcat_dataset
•	bridge2_dataset
•	bridge3_dataset
•	bridge4_dataset
Same across all 6 “xxx_dataset” directories, there are 3 folders inside: images, annotations and annotations_binary, where images folder contains RGB images, annotations folder contains multi-class labeled masks, and annotations_binary folder contains binary (water as 255 and non-water as 0) masks. The RGB values for each class are as follows:
•	Water: (128, 64, 128)
•	Boat: (0, 0, 230)
•	Bridge: (119, 11, 32)
•	Sky: (70, 130, 180)
•	Forest vegetation: (107, 142, 35)
•	Dry sediment: (220, 220, 0)
•	Drone itself: (10, 0, 0)
•	In-river obstacles: (150, 120, 90)

The images/masks are named alphabetically and correspondingly inside each “xxx_dataset” folder, where in “wabash_dataset” and “wildcat_dataset” images/masks also have their filenames containing “forward” or “downward” to differentiate 2 camera perspectives in the air.