The Optimal Solution of Feature Decomposition Based on the Mathematical Model of Nonlinear Landscape Garden Features

Shanshan Hu,Dawei Xu,Qi Meng,Udai Ali Al-Juboori

doi:10.2478/amns.2021.1.00070

Abstract

Abstract This Article aims at the current high idle rate of landscaped gardens and a single overall style. The article inputs the quantitative relationship programming of the dynamic model of the urban landscape ecological city system into the Grasshopper software to obtain the urban landscape parameter growth curve, and at the same time applies the nonlinear parameterized model method to the landscape design. The research found that the feature form of the landscape garden presented in the thesis is mainly based on the nonlinear transformation of the local analysis structure feature. In the end, the thesis deeply researches the existing operating modes based on the concept of nonlinear thinking. Furthermore, it combines with information technology to supplement and update the traditional landscape construction from different perspectives.

Highlights

The pattern in landscape ecology refers to the spatial pattern
The purpose of this paper is to study further the methods and characteristics of wavelet and semivariance for landscape pattern feature scale detection by using the IKONOSPAN
It can be seen that the IKONOSPAN1 m urban landscape with a size of 1024 rows and 1024 columns shows three levels of characteristic scales

Summary

Introduction

The pattern in landscape ecology refers to the spatial pattern. It includes the type, number, and spatial distribution and configuration of landscape components. The scale is expressed in terms of granularity and amplitude. The spatial granularity reflects the characteristic length, area, or volume represented by the identifiable units in the landscape. The amplitude refers to the continuous range or length of the research object in space or time. This paper uses the definition of spatial granularity to study the variation characteristics of landscape variables in spatial distribution

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