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Airborne Light Detection and Ranging (LiDAR) is widely used in digital elevation model (DEM) generation. However, the very large volume of LiDAR datasets brings a great challenge for the traditional serial algorithm. Using parallel computing to accelerate the efficiency of DEM generation from LiDAR points has been a hot topic in parallel geo-computing. Generally, most of the existing parallel algorithms running on high-performance clusters (HPC) were in process-paralleling mode, with a static scheduling strategy. The static strategy would not respond dynamically according to the computation progress, leading to load unbalancing. Additionally, because each process has independent memory space, the cost of dealing with boundary problems increases obviously with the increase in the number of processes. Actually, these two problems can have a significant influence on the efficiency of DEM generation for larger datasets, especially for those of irregular shapes. Thus, to solve these problems, we combined the advantages of process-paralleling with the advantages of thread-paralleling, forming a new idea: using process-paralleling to achieve a flexible schedule and scalable computation, using thread-paralleling inside the process to reduce boundary problems. Therefore, we proposed a hybrid process/thread parallel algorithm for generating DEM from LiDAR points. Firstly, at the process level, we designed a parallel method (PPDB) to accelerate the partitioning of LiDAR points. We also proposed a new dynamic scheduling strategy to achieve better load balancing. Secondly, at the thread level, we designed an asynchronous parallel strategy to hide the cost of LiDAR points' reading. Lastly, we tested our algorithm with three LiDAR datasets. Experiments showed that our parallel algorithm had no influence on the accuracy of the resultant DEM. At the same time, our algorithm reduced the conversion time from 112,486 s to 2342 s when we used the largest dataset (150 GB). The PPDB was parallelizable and the new dynamic scheduling strategy achieved a better load balancing. Furthermore, the asynchronous parallel strategy reduced the impact of LiDAR points reading. When compared with the traditional process-paralleling algorithm, the hybrid process/thread parallel algorithm improved the conversion efficiency by 30%. [ABSTRACT FROM AUTHOR]

The mega cities of China are faced with great pressure from conflict between huge land demand for construction use and limited resources. To improve this situation, it is necessary to slow the increasing rate of built-up land and even reduce the existing built-up land by improving land use efficiency. Herein, land use planning with urban sprawl deceleration is proposed. Land quotas are important tools for the control of land use planning in China, but the current quotas are mainly in the form of increment, thus cannot support land use planning with urban sprawl deceleration. To address these issues, we developed a model named “current-plan-requirement response (CPRR)”, to optimize the land quotas. With this model, we investigated the current status of land use, the process of land use planning, and the requirements of land use planning with urban sprawl deceleration in Shanghai. It was found that the current land quotas have provided somewhat inhabited conversion of arable land to built-up land, but scarcely any regulation of land use efficiency or protection of natural environment. Then, the land quotas were optimized and quota management recommendations were made. The optimized land quotas included four aspects of quotas: arable land protection, ecological conservation, scale constraint on built-up land and economical and intensive land use. These new land quotas could be used to guide reduction of built-up land and increase ecological land in China’s mega cities. It might also be beneficial for easing conflict between supply and demand of built-up land, for building an eco-friendly city land-use structure. [ABSTRACT FROM AUTHOR]

Object-based change detection (OBCD) has recently been receiving increasing attention as a result of rapid improvements in the resolution of remote sensing data. However, some OBCD issues relating to the segmentation of high-resolution images remain to be explored. For example, segmentation units derived using different segmentation strategies, segmentation scales, feature space, and change detection methods have rarely been assessed. In this study, we have tested four common unsupervised change detection methods using different segmentation strategies and a series of segmentation scale parameters on two WorldView-2 images of urban areas. We have also evaluated the effect of adding extra textural and Normalized Difference Vegetation Index (NDVI) information instead of using only spectral information. Our results indicated that change detection methods performed better at a medium scale than at a fine scale where close to the pixel size. Multivariate Alteration Detection (MAD) always outperformed the other methods tested, at the same confidence level. The overall accuracy appeared to benefit from using a two-date segmentation strategy rather than single-date segmentation. Adding textural and NDVI information appeared to reduce detection accuracy, but the magnitude of this reduction was not consistent across the different unsupervised methods and segmentation strategies. We conclude that a two-date segmentation strategy is useful for change detection in high-resolution imagery, but that the optimization of thresholds is critical for unsupervised change detection methods. Advanced methods need be explored that can take advantage of additional textural or other parameters. [ABSTRACT FROM AUTHOR]

Farmland preservation is a national issue in modern China. Most studies have focused on farmland preservation policies in the agricultural, commercial and financial industries but have devoted relatively little attention to land use planning. Land use planning is crucial for farmland preservation. This paper selected Dachang County, a typical rural county bordering Beijing, as the study area and reviews previous management policies, analyzes changes in farmland management and the socio-economic background over the past ten years. Next, this study presents land use planning decisions regarding farmland preservation measures. These measures included the establishment of farmland preservation zones and the creation of construction expansion zones and land consolidation zones. All of the findings would be useful for researchers as a reference for the study of land resource management and planning. [ABSTRACT FROM AUTHOR]

A reaction-based two-photon (TP) ratiometric fluorescence probe Z2 has been developed and successfully applied to detect and image fluoride ion in living cells and tissues. The Z2 probe was designed designed to utilize an ICT mechanism between n-butylnaphthalimide as a fluorophore and tert-butyldiphenylsilane (TBDPS) as a response group. Upon addition of fluoride ion, the Si-O bond in the Z2 would be cleaved, and then a stronger electron-donating group was released. The fluorescent changes at 450 and 540 nm, respectively, made it possible to achieve ratiometric fluorescence detection. The results indicated that the Z2 could ratiometrically detect and image fluoride ion in living cells and tissues in a depth of 250 µm by two-photon microscopy (TPM). [ABSTRACT FROM AUTHOR]