ALGORITHM FOR URBAN SPONTANEOUS GREEN SPACE DETECTION BASED ON OPTICAL SATELLITE REMOTE SENSING

被引：2

作者：

Ciezkowski, Wojciech ^{[1
]}

Sikorski, Piotr ^{[1
]}

Babanczyk, Piotr ^{[1
]}

Sikorska, Daria ^{[1
]}

Chormanski, Jaroslaw ^{[1
]}

机构：

[1] Warsaw Univ Life Sci SGGW, Inst Environm Engn, Dept Remote Sensing & Environm Assessment, Nowoursynowska 166, PL-02787 Warsaw, Poland

来源：

IGARSS 2020 - 2020 IEEE INTERNATIONAL GEOSCIENCE AND REMOTE SENSING SYMPOSIUM | 2020年

关键词：

remote sensing; urban ecology; mapping spontaneous vegetation; Sentinel-2; NDVI; WASTELANDS; CITIES;

D O I：

10.1109/IGARSS39084.2020.9324271

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

In this study we developed an algorithm for spontaneous green space identification in the cities. The algorithm was developed based on NDVI analyses (calculated from Sentinel-2 data) in Warsaw's green spaces, Poland. We analysed NDVI values in nearly 2000 points which allowed us to develop an algorithm for a distinction between managed and spontaneous vegetation, the algorithm results show that in all vegetation classes NDVI values obtained for managed vegetation are lower than for spontaneously occurring one. Application of algorithm requires a time series of satellite images, for all each of them, the NDVI threshold value is calculated. Finally, based on the number of exceedances of the threshold value each green space pixel is assigned to managed or spontaneous vegetation class. The validation shows that the algorithm achieves 70% accuracy for both classes.

引用

页码：4430 / 4433

页数：4

共 20 条

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