adding files, final ipynbs, and sav models #12
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changes to readme
Added space to the readme file
mhscience
reviewed
Jan 4, 2021
| @@ -3,7 +3,7 @@ | |||
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| The landslide_detector is a tool developed to detect landslides from optical remotely sensed images using Object-Based Image Analysis (OBIA) and Machine Learning (Random Forest classifier). | |||
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| I developed this tool to test the methodology proposed in [my master thesis](https://repository.tudelft.nl/islandora/object/uuid%3A52fe6b3b-ec0b-4cad-b51d-7798830688a4?collection=education) in Geomatics at Delft University of Technology. This implementation can be used to assist landslides experts/non-experts in detecting new landslides events and improve existing inventories. | |||
| This tool was developed to test the methodology proposed in [my master thesis](https://repository.tudelft.nl/islandora/object/uuid%3A52fe6b3b-ec0b-4cad-b51d-7798830688a4?collection=education) in Geomatics at Delft University of Technology. This implementation can be used to assist landslides experts/non-experts in detecting new landslides events and improve existing inventories. | |||
mhscience
reviewed
Jan 4, 2021
| @@ -29,8 +29,6 @@ Master in Geomatics @ Delft University of Technology | |||
| Contact: [email protected] | |||
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| #### Contributors | |||
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I can not delete people that contributed to this repository during the master thesis but I will modify the Readme to add the paper's contributor,, therefore the contributor's section will highlight who worked on what.
- Contributors
-- Paper XYZ (date)
-- Master Thesis (date)
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I see. I propose to make a new repository from scratch, on my account, in which I'll also add an href to this one.
mhscience
reviewed
Jan 4, 2021
| @@ -14,7 +14,7 @@ The tool is built using open source software: [Google Earth Engine(GEE)](https:/ | |||
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| - [Pre-processing script](https://github.com/mhscience/landslides_detection/blob/master/pre_processingGEE/pre_processing_thesis_mh.js) developed for Google Earth Engine. The script obtains cloud-free images from optical satellite imagery (Sentinel-2), extracts spectral and topographic features from Sentinel-2 and global Digital Elevation Model (DEM), and computes new landslides diagnostic features at pixel level | |||
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| - [Image segmentation program](https://github.com/mhscience/landslides_detection/tree/master/segmentation) developed in Python. Image segmentation is the first step towards the application of OBIA. It consists on the subdivision of an image into spatially continuous, disjoint, and relative homogeneous regions that refer to segments. This stage is implemented as a two-step approach: (a) an initial segmentation using a [k-means script](https://github.com/mhscience/landslides_detection/tree/master/segmentation/k_means_segmentation) (developed using [RSGISLib](https://www.rsgislib.org/)); (b) [merging algorithm script](https://github.com/mhscience/landslides_detection/tree/master/segmentation/merging_algorithm) using a region-growing implementation | |||
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We cannot remove this because it is linked to the master thesis. Let me think about how can I update this properly for the current paper.
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If you like my previous suggestion, we can go ahead like that. Hear from you
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newly made, for submission, in case a fork is not accepted.