Transectos de datos LiDAR: una estrategia de muestreo para estimar biomasa aérea en áreas forestales
DOI:
https://doi.org/10.21829/myb.2019.2531872Palabras clave:
franjas LiDAR, inventario forestal, muestreo, península de YucatánResumen
La estimación y el mapeo de la biomasa aérea sobre áreas extensas puede realizarse haciendo uso de las herramientas que ofrece la percepción remota. El objetivo de este estudio fue estimar la biomasa aérea de dos tipos de selva mediana: subperennifolia (SMSP) y subcaducifolia (SMSC) en la península de Yucatán, México, empleando métricas generadas a partir de datos Light Detection and Ranging (LiDAR). Se usaron datos de 365 unidades de muestreo del Inventario Nacional Forestal y de Suelos (INFyS) de México para calibrar modelos de biomasa aérea usando regresión lineal múltiple y Random Forest (RF). Con estos modelos se mapeó la biomasa aérea sobre franjas de datos LiDAR. El modelo de regresión transformado logró explicar la varianza en un 62% (RMSE = 41.44 Mg ha-1 para SMSP y 36.60 Mg ha-1 para SMSC) para ambos tipos de vegetación. Los modelos generados a través de RF lograron explicar la varianza en un 57% (RMSE = 40.73 Mg ha-1) para la SMSP y solo de 52% (RMSE = 35.10 Mg Ha-1) para la SMSC. El desfase entre la toma de datos en campo y LiDAR, así como el error en la precisión de las coordenadas de los sitios de inventario, son factores reconocidos que influyeron en los resultados. A pesar de lo anterior, las estimaciones obtenidas podrían servir de base para estimar el inventario completo de biomasa en el área de estudio incorporando datos espectrales derivados de un sensor remoto que cubra la totalidad de esta.Descargas
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