Update README.md

README.md

@@ -397,6 +397,7 @@ Extracting roads is challenging due to the occlusions caused by other objects an
 * [nia-road-baseline](https://github.com/SIAnalytics/nia-road-baseline) -> code for 2020 [paper](https://arxiv.org/abs/1908.08223): NL-LinkNet: Toward Lighter but More Accurate Road Extraction with Non-Local Operations
 * [IRSR-net](https://github.com/yangzhen1252/IRSR-net) -> code for 2022 [paper](https://ieeexplore.ieee.org/document/9785827): Lightweight Remote Sensing Road Detection Network
 * [hironex](https://github.com/johannesuhl/hironex) -> A python tool for automatic, fully unsupervised extraction of historical road networks from historical maps
+* [Road_detection_model](https://github.com/JonasImazon/Road_detection_model) -> code for 2022 [paper](https://www.mdpi.com/2072-4292/14/15/3625): Mapping Roads in the Brazilian Amazon with Artificial Intelligence and Sentinel-2
 
 ### Segmentation - Buildings & rooftops
 * [Semantic Segmentation on Aerial Images using fastai](https://medium.com/swlh/semantic-segmentation-on-aerial-images-using-fastai-a2696e4db127) uses U-Net on the Inria Aerial Image Labeling Dataset of urban settlements in Europe and the United States, and is labelled as a building and not building classes (no repo)
@@ -936,6 +937,7 @@ Generally speaking, change detection methods are applied to a pair of images to
 * [ChangeDetectionPCAKmeans](https://github.com/rulixiang/ChangeDetectionPCAKmeans) -> MATLAB implementation for Unsupervised Change Detection in Satellite Images Using Principal Component Analysis and k-Means Clustering.
 * [IRCNN](https://github.com/thebinyang/IRCNN) -> code for 2022 [paper](https://ieeexplore.ieee.org/abstract/document/9721897): IRCNN: An Irregular-Time-Distanced Recurrent Convolutional Neural Network for Change Detection in Satellite Time Series
 * [UTRNet](https://github.com/thebinyang/UTRNet) -> An Unsupervised Time-Distance-Guided Convolutional Recurrent Network for Change Detection in Irregularly Collected Images
+* [open-cd](https://github.com/likyoo/open-cd) -> an open source change detection toolbox based on a series of open source general vision task tools
 
 ## Time series
 More general than change detection, time series observations can be used for applications including improving the accuracy of crop classification, or predicting future patterns & events. Crop yield is very typically application and has its own section below
@@ -1448,6 +1450,8 @@ Measure surface contours & locate 3D points in space from 2D images. NeRF stands
 * [SatMVS](https://github.com/WHU-GPCV/SatMVS) -> code for 2021 paper: Rational Polynomial Camera Model Warping for Deep Learning Based Satellite Multi-View Stereo Matching
 * [ImpliCity](https://github.com/prs-eth/ImpliCity) -> reconstructs digital surface models (DSMs) from raw photogrammetric 3D point clouds and ortho-images with the help of an implicit neural 3D scene representation
 * [WHU-Stereo](https://github.com/Sheng029/WHU-Stereo) -> a large-scale dataset for stereo matching of high-resolution satellite imagery & several deep learning methods for stereo matching. Methods include StereoNet, Pyramid Stereo Matching Network & HMSM-Net
+* [Photogrammetry-Guide](https://github.com/mikeroyal/Photogrammetry-Guide) -> A guide covering Photogrammetry including the applications, libraries and tools that will make you a better and more efficient Photogrammetry development
+* [DSM-to-DTM](https://github.com/mdmeadows/DSM-to-DTM) -> Exploring the use of machine learning to convert a Digital Surface Model (e.g. SRTM) to a Digital Terrain Model
 
 ## Thermal Infrared
 * [The World Needs (a lot) More Thermal Infrared Data from Space](https://towardsdatascience.com/the-world-needs-a-lot-more-thermal-infrared-data-from-space-dbbba389be8a)