Satellite images from 2017-2018 of a single location show a decrease in forest cover from 17.94% to 17.08% due to deforestation detected using a U-Net image segmentation model. The U-Net model takes an image and returns a segmented image using convolutional and deconvolutional layers, allowing detection of deforestation areas over time to understand its regional impacts like increased global warming and disrupted ecological balance.
3. Deep Learning
and Satellite
Imaging
We are using satellite
images to figure out
over time how in a
region deforestation
occurred. We extracted
the deforestation area
using image segmentation
models.
4. Inside the
U-Net Model
• This takes an image and
returns another images.
• This is called conv and
deconvolution.
• In deep learning domain
it is called image
translation.
• Used in image
segmentation, image
enhancement.
5. U-Net Segmentation
to detect the
deforestation
• We can see how the
deforestation is
detected from the
satellite images in
the year of 2017 and
2018.
• This image is of a
single location only
and we can see that
forest cover
decreased from 17.94%
to 17.08%.
