Capability of GLAS/ICESat data to estimate forest canopy height and volume in mountainous forests of Iran
| Autor: | A. A. Darvishsefat, M Namiranian, Ibrahim Fayad, Valéry Gond, Nicolas Baghdadi, Jean-Stéphane Bailly, Manizheh Rajab Pourrahmati |
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| Přispěvatelé: | Territoires, Environnement, Télédétection et Information Spatiale (UMR TETIS), Centre de Coopération Internationale en Recherche Agronomique pour le Développement (Cirad)-AgroParisTech-Institut national de recherche en sciences et technologies pour l'environnement et l'agriculture (IRSTEA), University of Tehran, AgroParisTech, Laboratoire d'étude des interactions entre sols, agrosystèmes et hydrosystèmes (LISAH), Institut National de la Recherche Agronomique (INRA), Biens et services des écosystèmes forestiers tropicaux : l'enjeu du changement global (Cirad-Es-UPR 105 BSEF), Département Environnements et Sociétés (Cirad-ES), Centre de Coopération Internationale en Recherche Agronomique pour le Développement (Cirad)-Centre de Coopération Internationale en Recherche Agronomique pour le Développement (Cirad), Institut national de recherche en sciences et technologies pour l'environnement et l'agriculture (IRSTEA)-AgroParisTech-Centre de Coopération Internationale en Recherche Agronomique pour le Développement (Cirad), Laboratoire d'étude des Interactions Sol - Agrosystème - Hydrosystème (UMR LISAH), Institut de Recherche pour le Développement (IRD)-Institut National de la Recherche Agronomique (INRA)-Centre international d'études supérieures en sciences agronomiques (Montpellier SupAgro)-Institut national d’études supérieures agronomiques de Montpellier (Montpellier SupAgro), Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement (Institut Agro)-Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement (Institut Agro), Biens et services des écosystèmes forestiers tropicaux : l'enjeu du changement global (UPR BSEF), Centre de Coopération Internationale en Recherche Agronomique pour le Développement (Cirad) |
| Jazyk: | angličtina |
| Rok vydání: | 2015 |
| Předmět: |
Atmospheric Science
010504 meteorology & atmospheric sciences 0211 other engineering and technologies 02 engineering and technology forêt tropicale 01 natural sciences LIDAR Région d'altitude Forest cover COUVERT FORESTIER Mountain forest Hauteur Mathematics U10 - Informatique mathématiques et statistiques modèle de croissance forestière Houppier On board FOREST COVER protection de la forêt [SDE]Environmental Sciences Écosystème forestier F40 - Écologie végétale Télédétection gestion des ressources naturelles FORET DE MONTAGNE REMOTE SENSING Combinatorics Volume measurement Linear regression Mesure Computers in Earth Sciences TELEDETECTION 021101 geological & geomatics engineering 0105 earth and related environmental sciences Remote sensing Ressource forestière Tree canopy CANOPEE 15. Life on land MOUNTAIN FOREST K10 - Production forestière Volume (thermodynamics) Satellite Dendrométrie U30 - Méthodes de recherche Energy (signal processing) |
| Zdroj: | IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, IEEE, 2015, 8 (11), pp.5246-5261. ⟨10.1109/JSTARS.2015.2478478⟩ IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, IEEE, 2015, 8 (11), pp.5246-5261. ⟨10.1109/jstars.2015.2478478⟩ IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 2015, 8 (11), pp.5246-5261. ⟨10.1109/jstars.2015.2478478⟩ |
| ISSN: | 1939-1404 |
| DOI: | 10.1109/JSTARS.2015.2478478⟩ |
| Popis: | The importance of measuring forest biophysical properties for ecosystem health monitoring and forest management encourages researchers to find precise, yet low-cost methods especially in mountainous and large areas. In the present study, geoscience laser altimeter system (GLAS) on board Ice, Cloud, and land Elevation Satellite (ICESat) was used to estimate three biophysical characteristics of forests located in the north of Iran: 1) maximum canopy height ( ${\text {H}_{{\max}}}$ ); 2) Lorey’s height ( ${{\text H}_{\text{Lorey}}}$ ); and 3) forest volume (V). A large number of multiple linear regressions (MLR) and also random forest (RF) regressions were developed using different sets of variables including waveform metrics, principal components (PCs) produced from principal component analysis (PCA) and wavelet coefficients (WCs) generated from wavelet transformation (WT). To validate and compare models, statistical criteria were calculated based on a fivefold cross validation. Best model concerning the maximum height was an MLR ( ${\text {RMSE}} = {5.0}\;{\text m}$ ) which combined two metrics extracted from waveforms (waveform extent “ ${{\text W}_{\text{ext}}}$ ” and height at 50% of waveform energy “ ${{\text H}_{{50}}}$ ”), and one from digital elevation model (terrain index, TI). The mean absolute percentage error (MAPE) of maximum height estimates was 16.4%. For Lorey’s height, a simple MLR (including ${{\text W}_{\text{ext}}}$ and TI) represented the highest performance ( ${\text {RMSE}} = {5.1}\;{\text m}$ , ${\text {MAPE}} = {24.0}\% $ ). Generally, MLR models had a better performance when compared to the RF models. In addition, the accuracy of height estimations using waveform metrics was greater than those based on PCs or WCs. Concerning forest volume, regression models estimating volume directly from GLAS data led to a better result ( ${\text {RMSE}} = {128.8}\;{{\text m}^{3}}/\text {ha}$ ) rather than volume– ${{\text H}_{\text{Lorey}}}$ relationship ( ${\text {RMSE}} = {167.8}\;{{\text m}^{3}}/\text {ha}$ ). |
| Databáze: | OpenAIRE |
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