Optical methods require model inversion to infer plant area index (PAI) and woody area index (WAI) of leaf-on and leaf-off forest canopy from gap fraction or radiation attenuation measurements. Several inversion models have been developed previously, however, a thorough comparison of those inversion models in obtaining the PAI and WAI of leaf-on and leaf-off forest canopy has not been conducted so far. In the present study, an explicit 3D forest scene series with different PAI, WAI, phenological periods, stand density, tree species composition, plant functional types, canopy element clumping index, and woody component clumping index was generated using 50 detailed 3D tree models. The explicit 3D forest scene series was then used to assess the performance of seven commonly used inversion models to estimate the PAI and WAI of the leaf-on and leaf-off forest canopy. The PAI and WAI estimated from the seven inversion models and simulated digital hemispherical photography images were compared with the true PAI and WAI of leaf-on and leaf-off forest scenes. Factors that contributed to the differences between the estimates of the seven inversion models were analyzed. Results show that both the factors of inversion model, canopy element and woody component projection functions, canopy element and woody component estimation algorithms, and segment size are contributed to the differences between the PAI and WAI estimated from the seven inversion models. There is no universally valid combination of inversion model, needle-to-shoot area ratio, canopy element and woody component clumping index estimation algorithm, and segment size that can accurately measure the PAI and WAI of all leaf-on and leaf-off forest canopies. The performance of the combinations of inversion model, needle-to-shoot area ratio, canopy element and woody component clumping index estimation algorithm, and segment size to estimate the PAI and WAI of leaf-on and leaf-off forest canopies is the function of the inversion model as well as the canopy element and woody component clumping index estimation algorithm, segment size, PAI, WAI, tree species composition, and plant functional types. The impact of canopy element and woody component projection function measurements on the PAI and WAI estimation of the leaf-on and leaf-off forest canopy can be reduced to a low level (<4%) by adopting appropriate inversion models.

Interferometric fringes containing noise with complex distributions significantly contribute to phase unwrapping (PhU) failures in Synthetic Aperture Radar Interferometry (InSAR) technology. The study proposes an L2-Norm Quasi 3-D PhU-assisted multi-temporal InSAR strategy. Initially, the L2-Norm Quasi 3-D PhU (first spatial 2-D and then temporal 1-D PhU) is employed to reduce the phase gradient of interferograms with optimized networks. The advantage of this methodology is that the wrapped residual phase satisfies the phase triangle, thereby making it suitable for existing widely-used 2-D or 3-D PhU techniques. Subsequently, a popular PhU method is applied to the residual phase, which is smooth and continuous, thereby improving the accuracy of subsequent spatial PhU. The deformation rate, time series and number of PhU triplet closures demonstrate the reliability of the proposed method for the Pingtan Straits Rail-cum-Road Bridge and the Hong Kong-Zhuhai-Macao Bridge in China using the Sentinel-1A SAR dataset. The deformation results demonstrate that the bridge deformation is temperature-dependent, with the location of deformation being contingent upon the structural configuration of the bridge.

The correlation between road network accessibility and land use is mainly considered a spatial-topological relationship, thus making it difficult to reveal accurately. In consideration of the road speed limit and network structure, this paper constructed a road network accessibility model based on weighted spatial syntax. A correlation analysis between road network accessibility and land use was then conducted and compared with those based on relative asymmetry (RA) and normalized angular choice (NACH) by regarding the central district of Fuzhou City as an example. Results showed that the roads with good accessibility by RA and NACH were presented as ‘grid’ roads. The result of road network accessibility by weighted RA and NACH could better reflect the actual effect of road network accessibility than RA and NACH. Furthermore, the road network accessibility by weighted RA and NACH could improve the correlation analysis between road network accessibility and urban land use, especially in NACH. Results could provide a scientific reference for the urban planning and development.