Theses and Projects: Difference between revisions

Line 71:

Please contact Fei Gao [fei.gao@cs.uni-goettingen.de]

~~=== [Occupied] Image-to-Image Translation of Different Nightlight Image Types (B/M/P) ===~~

Nightlight intensities have been proven to be a good indicator for socio-economic status. However, for long-term temporal analyses their use can be challenging, as different satellites for sensing nightlight intensities operated at different times (DMSP OLS 1992-2014 and VIIRS 2012-2023). Both types differ not only in resolution, but there is also a big discrepancy in the optical appearance and value ranges. To obtain consistent nightlight images for temporal analysis, Image-to-Image Translation methods shall be used in this project/thesis for the conversion between both types. Finally the performance of the translated and original nightlight images for a regression on socio-economic indicators shall be evaluated.

~~Please contact Fabian Wölk [fabian.woelk@cs.uni-goettingen.de]~~

~~=== [Occupied] Satellite Image Indices and Machine Learning for Socio-economic Estimation (B/M/P) ===~~

There are several indices, which can be derived from satellite images. For example the Normalized Difference Vegetation Index (NDVI) indicates the presence and condition of vegetation, while the Normalized Difference Built-up Index (NDBI) indicates the presence of built-up areas such as buildings or roads. The distributions of these and other indices may have different explanatory power to estimate the socio-economic status of locations. Therefore in this project/thesis the regression performance of machine learning models - using statistics of these indices as features - to estimate socio-economic indicators shall be evaluated for the individual and also combined indices. Optionally, Convolutional Neural Networks (CNNs) can be applied additionally, which take the derived index images as input.

~~Please contact Fabian Wölk [fabian.woelk@cs.uni-goettingen.de]~~

=== * 3D natural hazard simulator ===

@@ Line 71: / Line 71: @@
 Please contact Fei Gao [fei.gao@cs.uni-goettingen.de]
-===  [Occupied]  Image-to-Image Translation of Different Nightlight Image Types (B/M/P) ===
-Nightlight intensities have been proven to be a good indicator for socio-economic status. However, for long-term temporal analyses their use can be challenging, as different satellites for sensing nightlight intensities operated at different times (DMSP OLS 1992-2014 and VIIRS 2012-2023). Both types differ not only in resolution, but there is also a big discrepancy in the optical appearance and value ranges. To obtain consistent nightlight images for temporal analysis, Image-to-Image Translation methods shall be used in this project/thesis for the conversion between both types. Finally the performance of the translated and original nightlight images for a regression on socio-economic indicators shall be evaluated.
-Please contact Fabian Wölk [fabian.woelk@cs.uni-goettingen.de]
-===  [Occupied] Satellite Image Indices and Machine Learning for Socio-economic Estimation (B/M/P) ===
-There are several indices, which can be derived from satellite images. For example the Normalized Difference Vegetation Index (NDVI) indicates the presence and condition of vegetation, while the Normalized Difference Built-up Index (NDBI) indicates the presence of built-up areas such as buildings or roads. The distributions of these and other indices may have different explanatory power to estimate the socio-economic status of locations. Therefore in this project/thesis the regression performance of machine learning models - using statistics of these indices as features - to estimate socio-economic indicators shall be evaluated for the individual and also combined indices. Optionally, Convolutional Neural Networks (CNNs) can be applied additionally, which take the derived index images as input.
-Please contact Fabian Wölk [fabian.woelk@cs.uni-goettingen.de]
 ===  * 3D natural hazard simulator  ===