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Due to their important role in maintaining temperature and soil moisture, agricultural plastic covers have been widely utilized around the globe for improving crop-growing conditions, which include both plastic-covered greenhouses (PCGs) and plastic-mulched farmlands (PMFs). However, it is a challenging and long-neglected issue to separate PCGs from PMFs due to their spectral similarity. The objective of this study is to propose a deep semantic segmentation model for accurate PCG and PMF mapping based on very high-resolution satellite images and to improve the model's spatial generalization capability using a transfer learning strategy. Specifically, the proposed semantic segmentation model has an encoder-decoder structure, where the encoder is composed of a new convolutional neural network for discriminative spatial feature learning, while the decoder utilizes a multi-task strategy to improve the predictions on the boundaries. Meanwhile, a transfer learning framework is adopted to increase mapping performance and generalization ability under limited samples. Experimental results in several typical regions across the Eurasian continent show that the proposed model could separate PCGs from PMFs accurately with a mean overall accuracy of 94.49% and an average mIoU of 0.8377. Ablation studies verify the role of encoder-decoder and transfer learning strategy in improving classification performance. [ABSTRACT FROM AUTHOR]

The visual perception of augmented reality (AR) geovisualization is significantly different from traditional controllable 2D and 3D visualization. In this study, we extended the rendering styles of color variables to include natural material color (NMC) and illuminating material color (IMC) and extended the size to include linear size (LS) and angular size (AS). Outdoor AR geovisualization user experiments were conducted, examining the guidance characteristics of five static variables (NMC, IMC, shape, AS, LS) and two dynamic variables (vibration, flicker). The results showed that the two dynamic variables provided the highest guidance, and among all the static variables, the order of guidance was shape, IMC, AS, NMC, and finally LS. This is a new finding that is different from the color, size, and shape guidance order in 2D visualization and the color, shape, and size order in 3D visualization. The results could be utilized to guide the selection of visual variables for symbol design in AR geovisualization. [ABSTRACT FROM AUTHOR]

Wheat is a major staple food crop in China. Accurate and cost-effective wheat mapping is exceedingly critical for food production management, food security warnings, and food trade policy-making in China. To reduce confusion between wheat and non-wheat crops for accurate growth stage wheat mapping, we present a novel approach that combines a random forest (RF) classifier with multi-sensor and multi-temporal image data. This study aims to (1) determine whether an RF combined with multi-sensor and multi-temporal imagery can achieve accurate winter wheat mapping, (2) to find out whether the proposed approach can provide improved performance over the traditional classifiers, and (3) examine the feasibility of deriving reliable estimates of winter wheat-growing areas from medium-resolution remotely sensed data. Winter wheat mapping experiments were conducted in Boxing County. The experimental results suggest that the proposed method can achieve good performance, with an overall accuracy of 92.9% and a kappa coefficient (κ) of 0.858. The winter wheat acreage was estimated at 33,895.71 ha with a relative error of only 9.3%. The effectiveness and feasibility of the proposed approach has been evaluated through comparison with other image classification methods. We conclude that the proposed approach can provide accurate delineation of winter wheat areas. [ABSTRACT FROM AUTHOR]

Due to advances in rendering techniques and hardware capability, stereoscopic 3D (s3D) visualization is becoming increasingly common in daily life. However, this does not change the fact that stereo effects and visual comfort depend greatly on how the related parameters are controlled during the production of the s3D images. In geo-virtual reality systems, which are important browsers for Digital Earth, the maintenance of these parameters is deeply related to the navigation process. Therefore, the navigation method in such systems requires special care. This paper presents a new flying method based on aCubemapstructure. The method defines aVehiclemodel and modifies the originalCubemapstructure by adding a front view camera during the navigation; it allows the users to fly through a virtual geographic environment with automatic speed control, smooth collision resolution, and dynamic adjustment of the s3D-related parameters. A user test was conducted to compare this new method with the original method based on theCubemapstructure. The results show that the new method performs better than the former one for it provides a convenient interaction experience with improved stereoscopic effect, and diminishes visual discomfort. [ABSTRACT FROM PUBLISHER]

Typhoons are usually accompanied by strong winds, heavy rain, storm surges and other disastrous events, and they are the most severe weather phenomena in the western part of the North Pacific Ocean. Visualisation is a key technology for analysing and presenting climate simulations and observations together with related social and ecological data. Virtual globes are a logical platform for visualising such geospatial data via the Internet. To implement interactive visualisation of typhoon data within virtual globes, this study provides a 3D texture-mapping algorithm to render volume textures on a globe. In addition, a systematic framework is proposed in which a hierarchical octree-based multiresolution data structure is implemented to organise the large volume dataset, and a graphics processing unit-based dynamic interpolation approach is proposed to obtain a smooth effect. Finally, the structure is combined with a level of detail strategy to enable the rendering of dynamic volumetric data at an acceptable interactive frame rate. To demonstrate the capabilities of this framework, data for a simulated typhoon event were rendered in World Wind, an open-source virtual globe. The experimental results demonstrate that the application of the proposed strategies can result in an interactive visualisation performance that renders typhoon data on virtual globes. [ABSTRACT FROM PUBLISHER]