Here we introduce so-far the largest subject-rated database of its kind, namely, "Effect of Paddy Rice vegetation on received signal strength between CC2538 SoC 32-bit Arm Cortex-M3 based sensor nodes operating at 2.4 GHz Radio Frequency (RF)". This database contains received signal strength measurements collected through campaigns in the IEEE 802.15.4 standard precision agricultural monitoring infrastructure developed for Paddy Rice crop monitoring from period 01/07/2020 to 03/11/2020.

Categories:
52 Views

Here we introduce so-far the largest subject-rated database of its kind, namely, "Effect of Millet vegetation on path-loss between CC2538 SoC 32-bit Arm Cortex-M3 based sensor nodes operating at 2.4 GHz Radio Frequency (RF)". This database contains received signal strength measurements collected through campaigns in the IEEE 802.15.4 standard precision agricultural monitoring infrastructure developed for millet crop monitoring from period 03/06/2020 to 04/10/2020.

Categories:
52 Views

The MATLAB data file “wind_speed_2015_2016_10minutely.mat” was obtained based on the original wind speed data downloaded from "Iowa Environmental Mesonet: AWOS Network Database" at the localities of Le Mars, Orange City, and Sheldon in Iowa, USA, recorded from 2015 to 2016. The raw data set has varying resolution, ranging from 5 to 10 min per sample. A fraction of missing measurements were filled in by interpolation. The resulting data-set was then re-sampled at a fixed rate of 10 min per sample, resulting in 105120 data points for each location.

Categories:
63 Views

These last decades, Earth Observation brought quantities of new perspectives from geosciences to human activity monitoring. As more data became available, artificial intelligence techniques led to very successful results for understanding remote sensing data. Moreover, various acquisition techniques such as Synthetic Aperture Radar (SAR) can also be used for problems that could not be tackled only through optical images. This is the case for weather-related disasters such as floods or hurricanes, which are generally associated with large clouds cover.

Instructions: 

The dataset is composed of 336 sequences corresponding to areas in West and South-East Africa, Middle-East, and Australia. Each time series is located in a given folder named with the sequence ID (0001... 0336).

Two json files, S1list.json and S2list.json are provided to describe respectively the Sentinel-1 and Sentinel-2 images.The keys are the total number of images in the sequence, the folder name, the geography of the observed area, and the description of each image in the series. The SAR images description contains also the URLs to download the images.Each image is described by its acquisition date, its label (FLOODING: boolean), a boolean (FULL-DATA-COVERAGE: boolean) indicating if the area is fully or partially imaged, and the file prefix. For SAR images the orbit (ASCENDING or DESCENDING) is also indicated.

The Sentinel-2 images were obtained from the Mediaeval 2019 Multimedia Satellite Task [1] and are provided with Level 2A atmospheric correction. For one acquisition, there are 12 single-channel raster images provided corresponding to the different spectral bands.

The Sentinel-1 images were added to the dataset. The images are provided with radiometric calibration and range doppler terrain correction based on the SRTM digital elevation model. For one acquisition, two raster images are available corresponding to the polarimetry channels VV and VH.

The original dataset was split into 267 sequences for the train and 67 sequences for the test. Here all sequences are in the same folder.

 

To use this dataset please cite the following papers:

Flood Detection in Time Series of Optical and SAR Images, C. Rambour,N. Audebert,E. Koeniguer,B. Le Saux,  and M. Datcu, ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, 2020, 1343--1346

The Multimedia Satellite Task at MediaEval2019, Bischke, B., Helber, P., Schulze, C., Srinivasan, V., Dengel, A.,Borth, D., 2019, In Proc. of the MediaEval 2019 Workshop

 

This dataset contains modified Copernicus Sentinel data [2018-2019], processed by ESA.

[1] The Multimedia Satellite Task at MediaEval2019, Bischke, B., Helber, P., Schulze, C., Srinivasan, V., Dengel, A.,Borth, D., 2019, In Proc. of the MediaEval 2019 Workshop

Categories:
727 Views

This dataset includes the synoptic data gathering from some stations in Fars province in Iran.

Categories:
38 Views

Four groups of wind speed series

Categories:
182 Views

An image dataset including five types of weather conditions (cloudy, sunny, foggy, rainy and snowy) was constructed.

 This dataset, called FWID, includes 4000 images for each weather category, leading to a total of 20000 images. 

Categories:
580 Views

An image dataset including five types of weather conditions (cloudy, sunny, foggy, rainy and snowy) was constructed.

 This dataset, called FWID, includes 4000 images for each weather category, leading to a total of 20000 images. 

Categories:
115 Views

An image dataset including five types of weather conditions (cloudy, sunny, foggy, rainy and snowy) was constructed.

 This dataset, called FWID, includes 4000 images for each weather category, leading to a total of 20000 images. 

Categories:
889 Views

Data from measurements in Åre during the winter 2018-2019.

Instructions: 

The attached documentation describes the measured parameters.

Files are in MATLAB (.mat) format.

Categories:
63 Views

Pages