Mapping the spatial distribution of stand age and aboveground biomass from Landsat time series analyses of forest cover loss in tropical dry forests

Remote Sensing in Ecology and Conservation

Juan Manuel Dupuy¹  Stephanie P. George‐Chacón¹  José Luis Hernández‐Stefanoni¹  Miguel Angel Castillo‐Santiago²  Jean François Mas³ 

[1] Centro de Investigación Científica de Yucatán A.C. Unidad de Recursos Naturales Calle 43130. Colonia Chuburná de Hidalgo. C.P. 97200 Mérida Yucatán México;El Colegio de la Frontera Sur Laboratorio de Análisis de Información Geográfica y Estadística Carretera Panamericana y Periférico sur s/n San Cristóbal de las Casas Chiapas CP 29290 Mexico;Laboratorio de análisis espacial Centro de Investigaciones en Geografía Ambiental Universidad Nacional Autónoma de México Campus Morelia Antigua Carretera a Pátzcuaro 8701, Col. Ex‐Hacienda de San José de La Huerta Morelia C.P. 58190 México;

关键词: forest cover change detection;    young forest;    NDVI time series;    aboveground biomass estimation;    remote sensing;   

DOI  :  10.1002/rse2.247

来源: DOAJ

【 摘 要 】

Abstract Spatial information on the timing of forest cover loss is important to identify and map stand age, which is a key factor driving the recovery of carbon pools and can also be used to estimate aboveground biomass (AGB) based on its relationship with stand age. Here, we estimated the spatial distribution of stand age and AGB of young forest (<20 years) in three types of tropical dry forest in the Yucatan peninsula using Landsat NDVI (normalized difference vegetation index) time series from 2000 to 2020. We estimated AGB based on chronosequence data and compared these results to reference field data and estimations obtained from remote‐sensing studies. The overall and user accuracy of the age map was high (95.7–99.9% and 87.35–98.5% respectively). However, lower producer accuracy values (from 31.2 to 67.2%) suggest an underestimation of the extension of young forests. We found a greater extent of young forests in the semi‐deciduous and deciduous forests compared to the semi‐evergreen ones. Mean AGB estimated from stand age (53.1 Mg ha−1) was lower than that estimated from remote‐sensing studies (67.5 to 95.2 Mg ha−1). These results indicate that spatial information of forest age can be accurately assessed from Landsat time series, and that the combination of stand age with chronosequence data can reduce the overestimation of AGB of recovering forests commonly found in remotely sensed data.

【 授权许可】

Unknown