• PDF / 912,277 Bytes
• 15 Pages / 547.087 x 737.008 pts Page_size
• 64 Downloads / 262 Views

DOWNLOAD

REPORT

---

Forest age mapping based on multiple-resource remote sensing data Xiguang Yang & Yuqi Liu & Zechuan Wu & Ying Yu & Fengri Li & Wenyi Fan

Received: 3 August 2020 / Accepted: 18 October 2020 # Springer Nature Switzerland AG 2020

Abstract Forest age is an important stand description factor and plays an important role in the carbon cycle of forest ecosystems. However, forest age data are typically lacking or are difficult to acquire at large spatial scale. Thus, it is important to develop a method of spatial forest age mapping. In this study, a method of forest age estimation based on multiple-resource remote sensing data was developed. Forest age was estimated by using average tree height estimated from the ICESat/GLAS and MODIS BRDF products. The results showed that forest age was significantly related to average tree height with a correlation coefficient of 0.752. Then, the average tree height was inversed using a waveform parameter extracted from ICESat/GLAS and was extended to continuous space with the help of the MODIS BRDF product. Thus, forest age mapping was realized. Lastly, the structure of forest age in the study area was evaluated. The results indicated that this method can be used to estimate forest age at the local scale and at large scale and can facilitate understandings of the real forest age structure features of a research area.

Keywords Forest age . Tree height . ICESat/GLAS . MODIS BRDF . Estimation X. Yang : Y. Liu : Z. Wu : Y. Yu : F. Li : W. Fan School of Forestry, Northeast Forestry University, Harbin, China X. Yang : Y. Liu : Z. Wu : Y. Yu : F. Li (*) : W. Fan Key Laboratory of Sustainable Forest Ecosystem Management-Ministry of Education, School of Forestry, Northeast Forestry University, Harbin, China e-mail: [email protected]

Introduction Forest age, which means the average age of the trees in a stand, is an important stand description factor and plays an important role in the forest carbon cycle, especially in the carbon strength (sink or source) of forest ecosystems (He et al. 2012; Zhang et al. 2012). Recently, an increasing number of studies have shown that forest age structure can be used to reflect the spatial and temporal changes of forest ecosystem carbon strength and can also be used as a variable to describe past disturbances, such as forest fires and clear-cutting (Aakala 2018; Bradford et al. 2008; Drake et al. 2011). Moreover, forest age is a main driver of forest structure and function (Banas et al. 2018; Kuuluvainen and Gauthier 2018). Thus, the forest age spatial distribution map has great significance for studying the carbon strength of forest ecosystems. Forest age is an investigated factor of the forest inventory implemented by the state forestry administration. Spatial forest age can be mapped by using these forest management inventory data (Dai et al. 2011). Dendrochronology data are another data source useful for mapping forest age (de Miranda et al. 2018; DeRose et al. 2017). However, acquisition of forest management inventory and dendrochronology data is diff