Onera Satellite Change Detection
# Nickname Score [%]
1 rcdaudt 95.74
2018 IEEE GRSS Data Fusion Contest: Data Fusion Classification Challenge
# Nickname Score [%]
1 Gaussian 80.78
2 Gaussian 80.77
3 dlrpba 80.74
4 dlrpba 80.46
5 dlrpba 80.31
6 AGTDA 79.79
7 Gaussian 79.34
8 IPIU 79.23
9 WULA2 78.77
10 WULA2 78.73
2018 IEEE GRSS Data Fusion Contest: Multispectral LiDAR Classification Challenge
# Nickname Score [%]
1 Gaussian 81.07
2 Gaussian 79.07
3 WULA2 78.67
4 WULA2 78.39
5 AGTDA 78.05
6 IPIU 78.01
7 IPIU 77.24
8 WULA2 77.16
9 GaoLei 75.82
10 AGTDA 75.43
2018 IEEE GRSS Data Fusion Contest: Hyperspectral Classification Challenge
# Nickname Score [%]
1 challenger 77.39
2 WULA2 76.59
3 XudongKang 76.37
4 XudongKang 76.15
5 XudongKang 76.12
6 XudongKang 76.00
7 XudongKang 75.97
8 WULA 75.33
9 WULA 75.08
10 WULA 74.81
2017 IEEE GRSS Data Fusion Contest
# Nickname Score [%]
1 NAVIA 76.15
2 WXYZ 74.94
3 WXYZ 74.45
4 NAVIA 73.63
5 WXYZ 73.38
6 AGTDA 72.63
7 AGTDA 72.63
8 camilasa 72.38
9 Fabricia 72.21
10 Fabricia 71.88
2015 IEEE GRSS Data Fusion Contest Dataset: Zeebruges
# Nickname Score [%]
1 rit1 87.93
2 rit1 87.91
3 RIT_YS 87.85
4 nshaud 87.31
5 RIT_YS 85.50
6 rit1 85.22
7 RIT_YS 85.22
8 rit1 84.82
9 rit1 83.63
10 rit1 83.51
San Francisco
# Nickname Score [%]
1 Adil 92.50
2 Adil 91.52
3 Adil 91.52
4 Adil 58.02
Flevoland
# Nickname Score [%]
no data
Avon12
# Nickname Score [%]
1 Nirmalan 95.19
2 EonRehman 95.08
3 EonRehman 95.08
4 EonRehman 95.08
5 pete 94.86
6 ST_IE 94.75
7 Tania 94.74
8 Nirmalan 94.70
9 SFOR 94.60
10 pete 94.59
Pavia
# Nickname Score [%]
1 EonRehman 85.34
2 EonRehman 81.86
3 utsav 81.49
4 EonRehman 81.36
5 utsav 81.22
6 EonRehman 81.03
7 utsav 80.57
8 rmkemker 80.38
9 rmkemker 80.01
10 rmkemker 79.98
Indian Pines
# Nickname Score [%]
1 EonRehman 95.26
2 EonRehman 94.64
3 EonRehman 91.59
4 rmkemker 91.32
5 rmkemker 91.10
6 wudixinxin 90.95
7 wudixinxin 90.93
8 wudixinxin 90.86
9 EonRehman 90.86
10 wudixinxin 90.81

GRSS Data and Algorithm Standard Evaluation website

Overview

The Standardized Remote Sensing Data Website of the IEEE Geoscience and Remote Sensing Society (GRSS) provides a set of community data sets and algorithm evaluation standards for use by the Earth observation community to support research, development, and testing of algorithms for remote sensing data products.

The website is aimed at remote sensing scientists, students, and professionals, who wish to evaluate the performances of their image analysis methods on freely available data against undisclosed test samples.

Currently, automated online evaluation of classification results from sample hyperspectral datasets is supported. The system is envisioned to grow to encompass more remote sensing modalities and types of processing results.

The website has been developed within the Standardized Algorithm and Data Evaluation Working Group of the GRSS Image Analysis and Data Fusion Technical Committee.

How to get the data and submit results

  • Register for an account and log in with your username and password.
  • Download the remotely sensed dataset you wish to classify along with the associated training data.
  • Apply your processing methods to generate a classification map and upload it to the website.
  • The website will automatically compute a set of classification accuracy parameters with respect to undisclosed test samples.
  • The top-10 results for each data set are reported on the website. You can also check your personal stats by logging in with your username and password.

Further information and useful hints from other users of this web site can be obtained through the LinkedIn Group of the IADF TC

Best displayed using Mozilla Firefox or Google Chrome. To navigate through the website, it is recommended to use the buttons on the right panel and not the back key.