广西-东盟多源遥感数据的森林高度反演及应用

doi:10.13474/j.cnki.11-2246.2024.0106

测绘通报 ›› 2024, Vol. 0 ›› Issue (1): 32-37,64.doi: 10.13474/j.cnki.11-2246.2024.0106

广西-东盟多源遥感数据的森林高度反演及应用

谢开翼^1,2,3, 陈瑞波⁴, 王志莉⁵, 王群⁵, 包俊帆^1,2,3, 朱宁宁⁶

1. 兰州交通大学测绘与地理信息学院, 甘肃兰州 730070;
2. 地理国情监测技术应用国家地方联合工程研究中心, 甘肃兰州 730070;
3. 甘肃省地理国情监测工程实验室, 甘肃兰州 730070;
4. 广西壮族自治区自然资源遥感院, 广西南宁 530201;
5. 襄阳市测绘研究院, 湖北襄阳 441003;
6. 武汉大学测绘遥感信息工程国家重点实验室, 湖北武汉 430079

收稿日期:2023-03-28 修回日期:2023-11-01 发布日期:2024-01-30
通讯作者: 朱宁宁。E-mail:ningningzhu@whu.edu.cn
作者简介:谢开翼(1999—),男,硕士生,研究方向为森林遥感。E-mail:11210898@stu.lzjtu.edu.cn
基金资助:
国家自然科学基金(42101446);中国博士后科学基金(2022T150488);广西壮族自治区自然资源遥感院(GXZC2021-GC-0392-GXZL);湖北省自然资源科研项目(ZRZY2022KJ22);自然资源部中国—东盟卫星遥感应用重点实验室开放资金

The inversion and application of forest height of multi-source remote sensing data in Guangxi-ASEAN region

XIE Kaiyi^1,2,3, CHEN Ruibo⁴, WANG Zhili⁵, WANG Qun⁵, BAO Junfan^1,2,3, ZHU Ningning⁶

1. Faculty of Geomatics, Lanzhou Jiaotong University, Lanzhou 730070, China;
2. Nation-Local Joint Engineering Research Center of Technologies and Applications for National Geographic State Monitoring, Lanzhou 730070, China;
3. Gansu Provincial Engineering Laboratory. for National Geographic State Monitoring, Lanzhou 730070, Clina;
4. Guangxi Zhuang Autonomous Region Institute of Natural Resources Remote Sensing, Nanning 530201, China;
5. Xiangyang Institute of Surveying and Mapping, Xiangyang 441003, China;
6. State Key Laboratory of Information Engineering in Surveying, Mapping and Remote Sensing, Wuhan University, Wuhan 430079, China

Received:2023-03-28 Revised:2023-11-01 Published:2024-01-30

摘要/Abstract

摘要： 森林生态系统在调节生态气候与碳循环方面发挥着重要作用,森林高度是衡量森林生态系统功能的重要参数。利用单一遥感数据获取森林冠层高度会受到多种制约。因此,本文使用星载激光雷达ICESat-2提供的高质量离散森林冠层高度点,结合Sentinel-1、Landsat 8及地形数据,采用随机森林方法建立不同影像特征组合森林冠层高度的回归模型,并分析各特征对森林高度反演的影响,最后将模型应用于广西森林冠层高度制图。试验结果表明,多源遥感数据可有效提高森林冠层高度反演精度,在所利用遥感数据中,特征重要性从大到小依次为光学特征、地形特征、SAR特征,“L8+SRTM+Sentinel-1+邻域均值”特征组合的反演精度最高,加入邻域均值特征进行森林冠层高度反演效果最佳,随机森林模型能精确绘制森林冠层高度。

关键词: 森林冠层高度, ICESat-2, Sentinel-1, Landsat 8, 广西-东盟

Abstract: Forest ecosystems play a critical role in regulating the ecological climate and carbon cycling, and forest height is a fundamental parameter for assessing their functional capacity. However, the acquisition of forest canopy height using single remote sensing data is subject to various constraints. Therefore, in this paper, we use high-quality discrete forest canopy height points from the spaceborne laser altimeter ICESat-2, combined with Sentinel-1, Landsat-8, and terrain data, to establish regression models of forest canopy height with different combinations of image features by using the random forest method, analyzing the impact of each feature on forest height inversion, and applying the model to forest canopy height mapping in Guangxi. The experimental results indicate that multisource remote sensing data effectively enhance the accuracy of forest canopy height estimation. Among the utilized remote sensing data, the feature importance descends in the order: optical features, terrain features, SAR features. The combination of “L8+SRTM+Sentinel-1+neighborhood mean” features achieves the highest accuracy in canopy height estimation, with the inclusion of neighborhood mean feature yielding the best results. The random forest model demonstrates precision in mapping forest canopy height.

Key words: forest canopy height, ICESat-2, Sentinel-1, Landsat 8, Guangxi-ASEAN

中图分类号:

P237

谢开翼, 陈瑞波, 王志莉, 王群, 包俊帆, 朱宁宁. 广西-东盟多源遥感数据的森林高度反演及应用[J]. 测绘通报, 2024, 0(1): 32-37,64.

XIE Kaiyi, CHEN Ruibo, WANG Zhili, WANG Qun, BAO Junfan, ZHU Ningning. The inversion and application of forest height of multi-source remote sensing data in Guangxi-ASEAN region[J]. Bulletin of Surveying and Mapping, 2024, 0(1): 32-37,64.

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广西-东盟多源遥感数据的森林高度反演及应用

The inversion and application of forest height of multi-source remote sensing data in Guangxi-ASEAN region

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