Vegetation type classification and vegetation cover percentage estimation in urban green zone using pleiades imagery

3rd International Symposium on LAPAN-IPB Satellite For Food Security and Environmental Monitoring 2016

地球科学;轻工业;生态环境科学

Trisakti, Bambang^1

Remote Sensing Application Center, LAPAN, Pekayon, Indonesia^1

关键词: Built environment;    Classification accuracy;    High resolution satellite imagery;    Local government;    Management activities;    Natural environments;    Supervised methods;    Urban green zones;   

Others  :  https://iopscience.iop.org/article/10.1088/1755-1315/54/1/012003/pdf
DOI  :  10.1088/1755-1315/54/1/012003

学科分类：环境科学（综合）

来源: IOP

【 摘 要 】

Open green space in the urban area has aims to maintain the availability of land as a water catchment area, creating aspects of urban planning through a balance between the natural environment and the built environment that are useful for the public needs. Local governments have to make the green zone plan map and monitor the green space changes in their territory. Medium and high resolution satellite imageries have been widely utilized to map and monitor the changes of vegetation cover as an indicator of green space area. This paper describes the use of pleaides imagery to classify vegetation types and estimate vegetation cover percentage in the green zone. Vegetation cover was mapped using a combination of NDVI and blue band. Furthermore, vegetation types in the green space were classified using unsupervised and supervised (ISODATA and MLEN) methods. Vegetation types in the study area were divided into sparse vegetation, low-medium vegetation and medium-high vegetation. The classification accuracies were 97.9% and 98.9% for unsupervised and supervised method respectively. The vegetation cover percentage was determined by calculating the ratio between the vegetation type area and the green zone area. These information are useful to support green zone management activities.