Pretraining data of SkySense++

This repository contains the data description and processing for the paper titled "SkySense++: A Semantic-Enhanced Multi-Modal Remote Sensing Foundation Model for Earth Observation." The code is in here

📢 Latest Updates

🔥🔥🔥 Last Updated on 2025.03.23 🔥🔥🔥

[2025.3.23] updated pretraining data list of representation-enhanced pretraining

[2025.3.14] updated optical images of JL-16 dataset (https://huggingface.co/datasets/KKKKKKang/JL-16)

[2025.3.12] updated sentinel-1 images and labels of JL-16 dataset 

[2025.3.9] updated pretrain and evaluation data

Pretrain Data

RS-Semantic Dataset

We conduct semantic-enhanced pretraining on the RS-Semantic dataset, which consists of 13 datasets with pixel-level annotations. Below are the specifics of these datasets.

Dataset
Modalities
GSD(m)
Size
Categories
Download Link

Five Billion Pixels
Gaofen-2
4
6800x7200
24
Download

Potsdam
Airborne
0.05
6000x6000
5
Download

Vaihingen
Airborne
0.05
2494x2064
5
Download

Deepglobe
WorldView
0.5
2448x2448
6
Download

iSAID
Multiple Sensors
-
800x800 to 4000x13000
15
Download

LoveDA
Spaceborne
0.3
1024x1024
7
Download

DynamicEarthNet
WorldView
0.3
1024x1024
7
Download

Sentinel-2*
10
32x32

Sentinel-1*
10
32x33

Pastis-MM
WorldView
0.3
1024x1024
18
Download

Sentinel-2*
10
32x32

Sentinel-1*
10
32x33

C2Seg-AB
Sentinel-2*
10
128x128
13
Download

Sentinel-1*
10
128x128

FLAIR
Spot-5
0.2
512x512
12
Download

Sentinel-2*
10
40x40

DFC20
Sentinel-2
10
256x256
9
Download

Sentinel-1
10
256x256

S2-naip
NAIP
1
512x512
32
Download

Sentinel-2*
10
64x64

Sentinel-1*
10
64x64

JL-16
Jilin-1
0.72
512x512
16
Download

Sentinel-1*
10
40x40

* for time-series data.

RS-Representation Dataset

The pretraining list is in the record rep_data_list.tar. The download and process scripts are in [Github](https://github.com/kang-wu/SkySensePlusPlus).

EO Benchmark

We evaluate our SkySense++ on 12 typical Earth Observation (EO) tasks across 7 domains: agriculture, forestry, oceanography, atmosphere, biology, land surveying, and disaster management. The detailed information about the datasets used for evaluation is as follows.

Domain
Task type
Dataset
Modalities
GSD
Image size
Download Link
Notes

Agriculture
Crop classification
Germany
Sentinel-2*
10
24x24
Download

Foresetry
Tree species classification
TreeSatAI-Time-Series
Airborne,
0.2
304x304
Download

Sentinel-2*
10
6x6

Sentinel-1*
10
6x6

Deforestation segmentation
Atlantic
Sentinel-2
10
512x512
Download

Oceanography
Oil spill segmentation
SOS
Sentinel-1
10
256x256
Download

Atmosphere
Air pollution regression
3pollution
Sentinel-2
10
200x200
Download

Sentinel-5P
2600
120x120

Biology
Wildlife detection
Kenya
Airborne
-
3068x4603
Download

Land surveying
LULC mapping
C2Seg-BW
Gaofen-6
10
256x256
Download

Gaofen-3
10
256x256

Change detection
dsifn-cd
GoogleEarth
0.3
512x512
Download

Disaster management
Flood monitoring
Flood-3i
Airborne
0.05
256 × 256
Download

C2SMSFloods
Sentinel-2, Sentinel-1
10
512x512
Download

Wildfire monitoring
CABUAR
Sentinel-2
10
5490 × 5490
Download

Landslide mapping
GVLM
GoogleEarth
0.3
1748x1748 ~ 10808x7424
Download

Building damage assessment
xBD
WorldView
0.3
1024x1024
Download

* for time-series data.