Blog - 52north - Sensor Web, Geoprocessing, Security & GeoRM, Geostatistics, Semantics, 3D, Ilwis, Earth Observation

Flood detection using Sentinel 1 images

November 5, 2021 by Sufian Zaabalawi Leave a Comment

Filed Under: 52°North, Earth Observation Tagged With: EO, Flood detection, ML, water recognition, Water Surface Classification

In a previous Blog-post, we implemented an application to identify water surfaces using Synthetic Aperture Radar (SAR) images produced by radar-based sensors. The main advantage of using this type of sensor is that it can overcome the limitation of optical spectral sensors in the case of clouds and weather conditions that block spectral reflectance. An example is the Sentinel 1 satellite, which uses microwaves that can penetrate haze, light rain and clouds to illuminate the earth and measure the backscatter and travel time of the transmitted waves reflected by objects on the ground. It has the clear advantage of being far less dependent on the weather and can acquire images at night to obtain near-real-time information and monitor the earth over a large area. Furthermore, SAR images provide a lower backscatter reflectance for water surfaces as compared to non-water surfaces. This significant difference can be used to distinguish water surfaces and other land areas.

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Water Surface Classification in Landsat 8 and Sentinel 1 Images

September 28, 2021 by Sufian Zaabalawi Leave a Comment

Filed Under: 52°North, Earth Observation Tagged With: Deep Learning algorithm, Landsat, Sentinel, Water Surface Classification

Deep Learning algorithms are being used more often to process remote sensing data. Data captured from satellite platforms requires reliable and generalized methods to periodically extract and analyse useful information. Environmental planners are becoming increasingly interested in applications, such as land cover mapping ranging from urban development to crop detection, to monitor climate change and wildfires.

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enviroCar App for iOS users – Final Blog Post

August 23, 2021 by khyatisaini Leave a Comment

Filed Under: 52°North, Citizen Science, Communities, enviroCar, GSoC Tagged With: envirocar, flutter, Google Summer of Code, gsoc2021

Introduction

enviroCar is a citizen science community that collects, shares, and analyzes floating car data for traffic management and the environment. It examines the open data and estimates the track count, average speed, relative speed, CO2 emission, fuel consumption, and hotspot analysis.

enviroCar app is a mobile application that provides features such as:

Recording tracks, exploring recorded tracks, and uploading tracks as open data for analysis.
Sharing data: Uploading data as open data for analysis that estimates CO2 emission, track count, average speed, relative speed, hotspot analysis.
Providing real-time data about the track, the distance covered, and the duration.

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enviroCar Platform Independent App Groundwork – Final Blog Post

August 23, 2021 by D Ajay Kumar 1 Comment

Filed Under: 52°North, enviroCar, GSoC Tagged With: 52°North, envirocar, flutter, GSoC, GSoC 2021

Introduction

enviroCar is an Android app that uses a car’s onboard sensors to collect data such as speed, fuel consumption, altitude, CO2 emission etc. using an OBD-II device to which it connects via Bluetooth. The data is then used by citizen scientists and traffic planners for research and development.

Although enviroCar app has been in use since 2013, it’s only been available to Android users so far. Therefore, the aim of this project was to create a cross-platform enviroCar app that would run on both Android as well as iOS devices. The idea was to lay the groundwork on which the community could later build the rest of the app. Happily, with great teamwork, time management and support from mentors, we came quite far from laying just the groundwork.

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