多光谱和雷达数据融合的各种方法在地上森林生物量建模中的应用

Q3 Agricultural and Biological Sciences

Folia Forestalia Polonica, Series A Pub Date : 2023-06-01 DOI:10.2478/ffp-2023-0006

D. Movchan, A. Bilous, L. Yelistratova, A. Apostolov, A. Hodorovsky

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引用次数: 0

摘要

摘要采用多元线性回归(MLR)、高通滤波(HPF)、强度色相饱和度(IHS)、小波变换(WT)和WT + IHS混合方法5种不同的数据融合技术对地上森林生物量(AGB)进行建模。研究采用RapidEye多光谱图像和PALSAR雷达图像作为遥感数据来源。利用切尔尼耶夫地区(乌克兰波利西亚)试验区的数据，建立了估算森林AGB的5个模型并进行了分析。计算了每个模型的相关性和最小-最大精度，以衡量模型的性能。在研究中使用的所有数据融合方法中，高通滤波方法显示出最高的效率。

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Application of various approaches of multispectral and radar data fusion for modelling of aboveground forest biomass

Abstract Five different data fusion techniques (multiple linear regression (MLR), high-pass filtering (HPF), intensity hue saturation (IHS), wavelet transformation (WT) and the hybrid method WT + IHS) have been applied to model the aboveground forest biomass (AGB) in this study. The RapidEye multispectral image and the PALSAR radar image were used in research as sources of remote sensing data. Five models for estimating forest AGB were built and analysed using data from test area in Chernihiv region (Ukrainian Polissya). Correlation and min–max accuracy have been calculated for each model to measure the model performance. Among all the data fusion approaches used in the study, the high-pass filtering method has shown the greatest efficiency.

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来源期刊

Folia Forestalia Polonica, Series A Agricultural and Biological Sciences-Forestry

CiteScore

1.30

自引率

0.00%

发文量

审稿时长

8 weeks

期刊介绍： FOLIA FORESTALIA POLONICA, SERIES A – FORESTRY is a forest science magazine addressed to scientists, administrators and policy-makers in forestry, agroforestry, ecology, environment and resource management. The language of publication is English and papers from any region of the world are welcome.