scholarly journals Modifying the site index model of sugi planted forests in Miyazaki Prefecture considering the effects of DEM quality and scale of digital terrain analysis

2015 ◽  
Vol 20 (2) ◽  
pp. 45-51 ◽  
Author(s):  
Yasushi Mitsuda ◽  
Satoshi Ito
Keyword(s):  
Site Index ◽  
Terrain Analysis ◽  
Digital Terrain Analysis ◽  
Planted Forests ◽  
Index Model ◽  
Digital Terrain ◽  
Site Index Model

scholarly journals A Method of Optimizing Terrain Rendering Using Digital Terrain Analysis

2021 ◽  
Vol 10 (10) ◽  
pp. 666
Author(s):  
Lei Zhang ◽  
Ping Wang ◽  
Chengyi Huang ◽  
Bo Ai ◽  
Wenjun Feng
Keyword(s):  
Large Scale ◽  
Frame Rate ◽  
Terrain Analysis ◽  
Image Pyramid ◽  
Digital Terrain Analysis ◽  
Terrain Rendering ◽  
Digital Terrain ◽  
Elevation Data ◽  
View Frustum Culling ◽  
Elevation Model

Terrain rendering is an important issue in Geographic Information Systems and other fields. During large-scale, real-time terrain rendering, complex terrain structure and an increasing amount of data decrease the smoothness of terrain rendering. Existing rendering methods rarely use the features of terrain to optimize terrain rendering. This paper presents a method to increase rendering performance through precomputing roughness and self-occlusion information making use of GIS-based Digital Terrain Analysis. Our method is based on GPU tessellation. We use quadtrees to manage patches and take surface roughness in Digital Terrain Analysis as a factor of Levels of Detail (LOD) selection. Before rendering, we first regularly partition the terrain scene into view cells. Then, for each cell, we calculate its potential visible patch set (PVPS) using a visibility analysis algorithm. After that, A PVPS Image Pyramid is built, and each LOD level has its corresponding PVPS. The PVPS Image Pyramid is stored on a disk and is read into RAM before rendering. Based on the PVPS Image Pyramid and the viewpoint’s position, invisible terrain areas that are not culled through view frustum culling can be dynamically culled. We use Digital Elevation Model (DEM) elevation data of a square area in Henan Province to verify the effectiveness of this method. The experiments show that this method can increase the frame rate compared with other methods, especially for lower camera flight heights.

Parallelization of Digital Terrain Analysis Algorithms

2013 ◽  
Vol 5 (6) ◽  
pp. 907-916
Author(s):  
Ling Jiang ◽  
Xuejun Liu ◽  
Guoan Tang ◽  
Xiaodong Song ◽  
Kai Liu ◽  
...  
Keyword(s):  
Terrain Analysis ◽  
Digital Terrain Analysis ◽  
Digital Terrain

Digital terrain analysis of a landslide on the loess tableland using high-resolution topography data

Landslides ◽  
2018 ◽  
Vol 16 (3) ◽  
pp. 617-632 ◽  
Author(s):  
Sheng Hu ◽  
Haijun Qiu ◽  
Yanqian Pei ◽  
Yifei Cui ◽  
Wanli Xie ◽  
...  
Keyword(s):  
High Resolution ◽  
Terrain Analysis ◽  
Digital Terrain Analysis ◽  
Digital Terrain ◽  
Topography Data

scholarly journals Case-based knowledge formalization and reasoning method for digital terrain analysis – application to extracting drainage networks

2016 ◽  
Vol 20 (8) ◽  
pp. 3379-3392 ◽  
Author(s):  
Cheng-Zhi Qin ◽  
Xue-Wei Wu ◽  
Jing-Chao Jiang ◽  
A-Xing Zhu
Keyword(s):  
Domain Knowledge ◽  
Case Based Reasoning ◽  
Preliminary Evaluation ◽  
Terrain Analysis ◽  
Digital Terrain Analysis ◽  
Digital Terrain ◽  
Drainage Networks ◽  
Building Process ◽  
Context Knowledge ◽  
Case Based

Abstract. Application of digital terrain analysis (DTA), which is typically a modeling process involving workflow building, relies heavily on DTA domain knowledge of the match between the algorithm (and its parameter settings) and the application context (including the target task, the terrain in the study area, the DEM resolution, etc.), which is referred to as application-context knowledge. However, existing DTA-assisted tools often cannot use application-context knowledge because this type of DTA knowledge has not been formalized to be available for inference in these tools. This situation makes the DTA workflow-building process difficult for users, especially non-expert users. This paper proposes a case-based formalization for DTA application-context knowledge and a corresponding case-based reasoning method. A case in this context consists of a series of indices that formalize the DTA application-context knowledge and the corresponding similarity calculation methods for case-based reasoning. A preliminary experiment to determine the catchment area threshold for extracting drainage networks has been conducted to evaluate the performance of the proposed method. In the experiment, 124 cases of drainage network extraction (50 for evaluation and 74 for reasoning) were prepared from peer-reviewed journal articles. Preliminary evaluation shows that the proposed case-based method is a suitable way to use DTA application-context knowledge to achieve a marked reduction in the modeling burden for users.

scholarly journals SITE QUALITY ESTIMATIONS BASED ON THE GENERALIZED ALGEBRAIC DIFFERENCE APPROACH: A CASE STUDY IN ÇANKIRI FORESTS

2018 ◽  
Vol 42 (3) ◽  
Author(s):  
Ugur Akbas ◽  
Muammer SENYURT
Keyword(s):  
Site Index ◽  
Site Quality ◽  
Model Parameters ◽  
Successful Model ◽  
Index Model ◽  
Prediction Technique ◽  
Algebraic Difference ◽  
Pine Stands ◽  
Site Index Model ◽  
Generalized Algebraic Difference Approach

ABSTRACT In this study, it is aimed that the dynamic site index models were developed for Crimean Pine stands in Sarikaya-Cankiri forests located in middle northern Turkey. The data for this study are 153 sample trees obtained from the Crimean Pine stands. In modeling relationships between height and age of dominant or co-dominant trees, some dynamic site index equations such as Chapman-Richards (M1, M2, M3), Lundqvist (M4 and M6), Hossfeld (M5), Weibull (M7) and Schumacher (M8) based on the Generalized Algebraic Difference Approach (GADA) were used. The estimations for these eight-dynamic site index model parameters with well as various statistical values were obtained using the nonlinear regression technique. Among these equations, the Chapman-Richards’s equation, M3, was determined to be the most successful model, with accounted for 89.03 % of the total variance in height-age relationships with MSE: 1.7633, RMSE: 1.3279, SSE: 1165.6, Bias: -0.0380. After determination of the best predictive model, ARMA (1, 1) autoregressive prediction technique was used to account autocorrelation problems for time-series height measurements. When ARMA autoregressive prediction technique was applied to the Chapman-Richards function for solving autocorrelation problem, these success statistics were improved as SSE: 868.7, MSE: 1.3183, RMSE: 1.1482, Bias: -0.06369, R2: 0.918. Also, Durbin-Watson statistics displayed that autocorrelation problem was solved by the use of ARMA autoregressive prediction technique; DW test value=1.99, DW<P=0.5622, DW>P=0.4378. The dynamic site index model that was developed has provided results compatible with the growth characteristics expected in the modeling of height-age relations, such as polymorphism, multiple asymptote, and base-age invariance.

Development of Site Index Model for Styrax japonica

2019 ◽  
Vol 53 (4) ◽  
pp. 13-18
Author(s):  
Joon Hyung Park ◽  
◽  
Kwang Soo Lee ◽  
Yeong Mo Sonk ◽  
Su Young Jung ◽  
...  
Keyword(s):  
Site Index ◽  
Index Model ◽  
Site Index Model ◽  
Styrax Japonica

A calibrateable site index model for Pinus kesiya plantations in southeastern Africa

2002 ◽  
Vol 32 (11) ◽  
pp. 1916-1928 ◽  
Author(s):  
Kalle Eerikäinen ◽  
Danaza Mabvurira ◽  
Ladislaus Nshubemuki ◽  
Jussi Saramäki
Keyword(s):  
Random Parameter ◽  
Site Index ◽  
Stand Age ◽  
Random Parameters ◽  
Index Model ◽  
Forest Inventories ◽  
Pinus Kesiya ◽  
Dominant Height ◽  
Random Parameter Model ◽  
Site Index Model

The aim of the study was to develop a site index model for Pinus kesiya Royle ex Gordon plantations in southeastern Africa based on the relationship between the dominant height and stand age. Conversely, analysis of dominant height and age data showed that the growth patterns of plantations were different. In addition, the asymptotes and forms of standwise dominant height curves varied within plantations. In developing a common site index model, instead of using the more common approach of estimating separate dominant height–age models for different plantations or sites, a mean curve approach based on a linear random parameter model with fixed and random parameters was applied. The random parameter model of this study was calibrated by predicting random parameters for the plantation and stand effects, in accordance with the standard linear prediction theory. The analyses showed that the calibration of the dominant height model was an efficient method to obtain reliable dominant height predictions of a stand, particularly when several dominant height–age observations from different stands of a plantation and at least one measured dominant height and stand age of a target stand are available. This is the case in many forest inventories based on temporary samples, i.e., cross-sectional data. The new site index model is a useful tool for use in different mensurational applications, and its properties can efficiently be utilized for example in forest inventories of P. kesiya plantations in southeastern Africa.

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