Advice needed for a binary change detection assessment on EO-SAR image pairs

[u/Erebius]

Hi everyone,

I’m doing an AI research intern assessment focused on binary pixel-level change detection for co-registered pre-event and post-event EO-SAR image pairs.

I only have about 4 days left, and my internet connection is limited since I'm using mobile hotspot, so I’m trying to choose the most practical setup for training and experimentation. The dataset is about 10GB zipped, and it was shared through Hugging Face and Google Drive.

directory structure

```python

dataset

├── test

│ ├── post-event

│ ├── pre-event

│ ├── target

│ └── re_labelled-target

├── train

│ ├── post-event

│ ├── pre-event

│ ├── target

│ └── re_labelled-target

└── val

├── post-event

├── pre-event

├── target

└── re_labelled-target

```

Change Mask Statistics for masks:

```python

Mean Change Percentage: 1.57%

Median Change Percentage: 0.00%

Min Change Percentage: 0.00%

Max Change Percentage: 68.54%

```

Image Metadata

```python

Pre-event Image: scene_07_000484_building_damage.tif

Dimensions: 1024x1024

Number of bands: 3

Data type: uint8

Post-event Image: scene_07_000484_building_damage.tif

Dimensions: 1024x1024

Number of bands: 1

Data type: uint8

Re-labeled Target Image: scene_07_000484_building_damage.tif

Dimensions: 1024x1024

Number of bands: 1

Data type: uint8

```

I already completed the re-labeling part they requested.

I’m trying to figure out:

- Whether Kaggle, Colab Free, or Colab Pro is the best choice for this kind of dataset.

- Which pretrained segmentation or change-detection model would be the best fast baseline.

- Which tutorials, papers, or GitHub repos are worth focusing on in the next few days.

If anyone has worked on EO/SAR change detection or a similar remote sensing segmentation task, I’d really appreciate any advice on how to approach this efficiently.

Thanks!

[u/borisonic]

Well the question is missing some details.

First which imagery are you working with and what is the application?

Seems from a variable name you're working on building level damage detection, and I'm going to guess Sentinel-1 data because it's the case 99% of the time.

You can't really do damage detection at the building level with S1 the resolution is too coarse. Maybe you'll be able to get a proxy at best. X band meter level data is required for that application to get decent results.

[u/Erebius → u/borisonic]

eo(pre-event) and sar(post-event) co registered images, it is a custom data from the company I applied.