Correlation analysis of satellite-based mangrove index and mangrove forest health at Segara Anakan Cilacap, Central Java, Indonesia

• Published in: IOP conference series. Earth and environmental science Vol. 500; no. 1; pp. 12050 - 12054
• Main Authors: Winarso, Gathot, Kamal, Muhammad, Rosid, Syamsu, Asriningrum, Wikanti, Supriyatna, Jatna
• Format: Journal Article
• Language: English
• Published: Bristol IOP Publishing 01.06.2020
• Subjects: Air temperature; Biodiversity; Correlation analysis; Mangrove swamps; Normalized difference vegetative index; Parameter identification; Planting density; Seedlings; Soil density; Soil moisture; Soil temperature; Spectral reflectance; Vegetation; Vegetation index; Visual fields; Central Java Indonesia; Indonesia
• ISSN: 1755-1307; 1755-1315
• DOI: 10.1088/1755-1315/500/1/012050

This study aims to introduce satellite-based Mangrove Index to substitute mangrove health indicator based on Normalized Difference Vegetation Index (NDVI) when it was failed to represent mangrove health at Segara Anakan mangrove area, Cilacap, Central Java, Indonesia. The Mangrove Index has potential to be implemented as indicator of mangrove health because it is deduced from two main characteristics of mangrove forest, which are vegetation condition and hydro-period parameters. Previous mangrove health identification was mainly conducted using visual analysis during the field check and used previous reports that could not be statistically analyzed. The correlation between Mangrove Index and mangrove health condition was analyzed to measure the degree and form of relationship between them as a basis for mangrove health modelling. We conducted paper review to synthesize the mangrove health condition and enriched our analysis by incorporating as many field data as possible related to canopy cover, stand density, seedling density, stake density, biodiversity index, soil moisture, pH, soil temperature, air temperature and air humidity. Our finding shows that the degree of correlation for each parameter were low. The maximum coefficient of determination (R2) of 0.5 was found for combination between stand and sapling density divided by soil moisture. The combination these parameters was selected because Mangrove Index was produced from image bands that has high spectral reflectance response to vegetation (NIR) and soil moisture (SWIR). This result is not a final because limited parameters were incorporated in the analysis. Further deeper analysis to simulate all field parameters need to be done in the future.