A Multiscale Quantification of Leaf Area Index with Unmanned Aerial Vehicle and SPOT-7 Satellite Imageries: A case of Kuala Lumpur, Malaysia.

The statutory planning of the urban landscape of Kuala Lumpur (KL) has been solely relied on a rigid and fixed quantitative specification without ecological evaluation, resulting in the loss of biodiversity, degradation of urban ecosystem services and liveability. Past research in the area of quantitative urban green space (UGS) planning and ecology were mainly concentrated in the provision, accessibility, and connectivity of UGS, but lacking in the ecological quality dimension. This paper intends to fill the knowledge gap by quantifying the ecological quality of UGS in multiple scales from tree, park, to city level with unmanned aerial vehicle (UAV) to map the leaf area index (LAI) in the city of KL. The estimation of KL LAI involves a two-step processes. In the first step, 9 UGSs under the management of local authority were selected for the mapping of the distribution of Normalized Differential Vegetation Index (NDVI) with Unmanned Aerial Vehicle (UAV). Concurrently, rigorous field works are conducted to sample field LAI of selected trees in all of the UGSs with AccuPAR LP80 Ceptometer. UGS LAI are estimated with regression of UAV NDVI and field LAI. Analysis of the result shows that there is a moderately strong relationship (R² = 0.56, RMSE =0.33) between UAV NDVI and field LAI and the established statistical equation is used for the estimation of UGS LAI covering all the parks. In the second step, the statistical relationship was upscaled to the entire city level with UGS LAI and SPOT-7 NDVI data (R² =0.50, RMSE = 0.94). The multiscale estimation of LAI provides an effective indicator of the landscape ecological performance among the different electoral area where targeted landscape enhancement and remediation policies can be formulated to improve urban sustainability. [ABSTRACT FROM AUTHOR]