Remote sensing of seasonal variability monitoring of forest LAI over mountain areas in Beijing

Leaf area index (LAI) is an important parameter of vegetation ecosystems, which can reflect the growth status of vegetation. In this study, multi-temporal Landsat5 TM images covering Jiufeng forest in the northwest mountain areas of Beijing were acquired. In-situ forest LAI values were measured synchronously using Hemispherical Photography. By correlation analysis of three vegetation indexes (NDVI, EVI and TGDVI) and LAI, it was found that the correlation between LAI and NDVI in exponential form behaved a good relativity. This model was applied in mapping forest LAI distributions in different time. Moreover, compared with the previous finding regardless of vegetation type, the sensitivity of the models between vegetation indexes and LAI can be improved both in broadleaf and mixed forests, while a little decrease in conifer stands. But, the accuracy of all models reached a significant level.