Monitoring of lake dynamics

Last update: Jun 23, 2022

Overview

Monitoring of lake dynamics

This is a program that uses multi-source remote sensing data to monitor the dynamic changes of lakes. The detailed introduction of the modified procedure and specific application examples will be presented in the form of a paper in the near future.

Multisource satellite data processing

The program supports the processing of multi-source satellite images (Landsat, Sentinel) and multi-source satellite altimetry data(CryoSat2, ICESat2, Sentinel3). Including extracting lake water bodies from GSW data, extracting lake area, and extracting lake water level.

Instructions for use

To use this program, you need to use the water index image as input. It is recommended to use Google earth engine(GEE) to calculate the water index. Other precautions are detailed in the program.

Requirements

Please use python 3.7. Other dependent packages include gdal, opencv, etc.,in requirements.txt. Just follow the prompts and click install.

Citation

Please cite our preliminary work if you use this code:
Zhang C, Lv A, Zhu W, Yao G, Qi S. Using Multisource Satellite Data to Investigate Lake Area, Water Level, and Water Storage Changes of Terminal Lakes in Ungauged Regions. Remote Sensing. 2021; 13(16):3221. https://doi.org/10.3390/rs13163221.
More detailed code explanations and application examples are under review in the form of academic articles.

Welcome to communicate

Your comments and suggestions are welcome

You might also like...

This solution helps you deploy Data Lake Infrastructure on AWS using CDK Pipelines.

CDK Pipelines for Data Lake Infrastructure Deployment This solution helps you deploy data lake infrastructure on AWS using CDK Pipelines. This is base

66 Nov 23, 2022

Reinforcement Learning with Q-Learning Algorithm on gym's frozen lake environment implemented in python

Reinforcement Learning with Q Learning Algorithm Q learning algorithm is trained on the gym's frozen lake environment. Libraries Used gym Numpy tqdm P

1 Nov 10, 2021

HTTP(s) "monitoring" webpage via FastAPI+Jinja2. Inspired by https://github.com/RaymiiOrg/bash-http-monitoring

python-http-monitoring HTTP(s) "monitoring" powered by FastAPI+Jinja2+aiohttp. Inspired by bash-http-monitoring. Installation can be done with pipenv

39 Aug 26, 2022

Monitoring plugin to check network interfaces with Icinga, Nagios and other compatible monitoring solutions

check_network_interface - Monitor network interfaces This is a monitoring plugin for Icinga, Nagios and other compatible monitoring solutions to check

3 Nov 15, 2022

Monitoring plugin to check disk io with Icinga, Nagios and other compatible monitoring solutions

check_disk_io - Monitor disk io This is a monitoring plugin for Icinga, Nagios and other compatible monitoring solutions to check the disk io. It uses

3 Nov 15, 2022

Logging-monitoring-instrumentation - A brief repository on logging monitoring and instrumentation in Python

logging-monitoring-instrumentation A brief repository on logging monitoring and

6 Feb 17, 2022

Dataset Cartography: Mapping and Diagnosing Datasets with Training Dynamics

Dataset Cartography Code for the paper Dataset Cartography: Mapping and Diagnosing Datasets with Training Dynamics at EMNLP 2020. This repository cont

125 Dec 22, 2022

NetworkX is a Python package for the creation, manipulation, and study of the structure, dynamics, and functions of complex networks.

12k Jan 2, 2023

PyDy, short for Python Dynamics, is a tool kit written in the Python

PyDy, short for Python Dynamics, is a tool kit written in the Python programming language that utilizes an array of scientific programs to enable the study of multibody dynamics. The goal is to have a modular framework and eventually a physics abstraction layer which utilizes a variety of backends that can provide the user with their desired workflow

307 Jan 1, 2023

Code for ECCV 2020 paper "Contacts and Human Dynamics from Monocular Video".

Contact and Human Dynamics from Monocular Video This is the official implementation for the ECCV 2020 spotlight paper by Davis Rempe, Leonidas J. Guib

207 Jan 5, 2023

Pytorch code for "State-only Imitation with Transition Dynamics Mismatch" (ICLR 2020)

This repo contains code for our paper State-only Imitation with Transition Dynamics Mismatch published at ICLR 2020. The code heavily uses the RL mach

20 Sep 8, 2022

PyTorch Code of "Memory In Memory: A Predictive Neural Network for Learning Higher-Order Non-Stationarity from Spatiotemporal Dynamics"

Memory In Memory Networks It is based on the paper Memory In Memory: A Predictive Neural Network for Learning Higher-Order Non-Stationarity from Spati

12 May 30, 2022

BridgeWalk is a partially-observed reinforcement learning environment with dynamics of varying stochasticity.

BridgeWalk is a partially-observed reinforcement learning environment with dynamics of varying stochasticity. The player needs to walk along a bridge to reach a goal location. When the player walks off the bridge into the water, the current will move it randomly until it gets washed back on the shore. A good agent in this environment avoids this stochastic trap

6 Jun 13, 2022

VID-Fusion: Robust Visual-Inertial-Dynamics Odometry for Accurate External Force Estimation

VID-Fusion VID-Fusion: Robust Visual-Inertial-Dynamics Odometry for Accurate External Force Estimation Authors: Ziming Ding , Tiankai Yang, Kunyi Zhan

86 Nov 18, 2022

Official PyTorch implementation of "Physics-aware Difference Graph Networks for Sparsely-Observed Dynamics".

Physics-aware Difference Graph Networks for Sparsely-Observed Dynamics This repository is the official PyTorch implementation of "Physics-aware Differ

46 Nov 20, 2022

source code for https://arxiv.org/abs/2005.11248 "Accelerating Antimicrobial Discovery with Controllable Deep Generative Models and Molecular Dynamics"

Accelerating Antimicrobial Discovery with Controllable Deep Generative Models and Molecular Dynamics This work will be published in Nature Biomedical

71 Nov 15, 2022

PyBullet CartPole and Quadrotor environments—with CasADi symbolic a priori dynamics—for learning-based control and reinforcement learning

safe-control-gym Physics-based CartPole and Quadrotor Gym environments (using PyBullet) with symbolic a priori dynamics (using CasADi) for learning-ba

300 Dec 28, 2022

This is the open-source reference implementation of the SIGGRAPH 2021 paper Intersection-free Rigid Body Dynamics.

Robust, intersection-free, simulations of rigid bodies.

93 Dec 23, 2022

Pytorch implementation of CVPR2020 paper “VectorNet: Encoding HD Maps and Agent Dynamics from Vectorized Representation”

VectorNet Re-implementation This is the unofficial pytorch implementation of CVPR2020 paper "VectorNet: Encoding HD Maps and Agent Dynamics from Vecto

120 Jan 6, 2023

Monitoring of lake dynamics

Related tags

Overview

Monitoring of lake dynamics

Multisource satellite data processing

Instructions for use

Requirements

Citation

Welcome to communicate

You might also like...

This solution helps you deploy Data Lake Infrastructure on AWS using CDK Pipelines.

Reinforcement Learning with Q-Learning Algorithm on gym's frozen lake environment implemented in python

HTTP(s) "monitoring" webpage via FastAPI+Jinja2. Inspired by https://github.com/RaymiiOrg/bash-http-monitoring

Monitoring plugin to check network interfaces with Icinga, Nagios and other compatible monitoring solutions

Monitoring plugin to check disk io with Icinga, Nagios and other compatible monitoring solutions

Logging-monitoring-instrumentation - A brief repository on logging monitoring and instrumentation in Python

Dataset Cartography: Mapping and Diagnosing Datasets with Training Dynamics

NetworkX is a Python package for the creation, manipulation, and study of the structure, dynamics, and functions of complex networks.

PyDy, short for Python Dynamics, is a tool kit written in the Python

Code for ECCV 2020 paper "Contacts and Human Dynamics from Monocular Video".

Pytorch code for "State-only Imitation with Transition Dynamics Mismatch" (ICLR 2020)

PyTorch Code of "Memory In Memory: A Predictive Neural Network for Learning Higher-Order Non-Stationarity from Spatiotemporal Dynamics"

BridgeWalk is a partially-observed reinforcement learning environment with dynamics of varying stochasticity.

VID-Fusion: Robust Visual-Inertial-Dynamics Odometry for Accurate External Force Estimation

Official PyTorch implementation of "Physics-aware Difference Graph Networks for Sparsely-Observed Dynamics".

source code for https://arxiv.org/abs/2005.11248 "Accelerating Antimicrobial Discovery with Controllable Deep Generative Models and Molecular Dynamics"

PyBullet CartPole and Quadrotor environments—with CasADi symbolic a priori dynamics—for learning-based control and reinforcement learning

This is the open-source reference implementation of the SIGGRAPH 2021 paper Intersection-free Rigid Body Dynamics.

Pytorch implementation of CVPR2020 paper “VectorNet: Encoding HD Maps and Agent Dynamics from Vectorized Representation”

Owner

PyDy, short for Python Dynamics, is a tool kit written in the Python

BridgeWalk is a partially-observed reinforcement learning environment with dynamics of varying stochasticity.

Life Dynamics for python

TinyBar - Tiny MacOS menu bar utility to track price dynamics for assets on TinyMan.org

Stock Monitoring

Sample python script for monitoring Rocketchat database and get statistics of users.

Performance monitoring and testing of OpenStack

Linux Security and Monitoring Scripts

InverterApi - This project has been designed to take monitoring data from Voltronic, Axpert, Mppsolar PIP, Voltacon, Effekta

A micro-service that can be extended to help in monitoring systems