Comparison of Airborne LiDAR and Satellite Hyperspectral Remote Sensing to Estimate Vascular Plant Richness in Deciduous Mediterranean Forests of Central Chile
The Andes foothills of central Chile are characterized by high levels of floristic diversity in a scenario, which offers little protection by public protected areas. Knowledge of the spatial distribution of this diversity must be gained in order to aid in conservation management. Heterogeneous envir...
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MDPI AG
2015-03-01
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| Series: | Remote Sensing |
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| Online Access: | http://www.mdpi.com/2072-4292/7/3/2692 |
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| author | Andrés Ceballos Jaime Hernández Patricio Corvalán Mauricio Galleguillos |
| author_facet | Andrés Ceballos Jaime Hernández Patricio Corvalán Mauricio Galleguillos |
| author_sort | Andrés Ceballos |
| collection | DOAJ |
| description | The Andes foothills of central Chile are characterized by high levels of floristic diversity in a scenario, which offers little protection by public protected areas. Knowledge of the spatial distribution of this diversity must be gained in order to aid in conservation management. Heterogeneous environmental conditions involve an important number of niches closely related to species richness. Remote sensing information derived from satellite hyperspectral and airborne Light Detection and Ranging (LiDAR) data can be used as proxies to generate a spatial prediction of vascular plant richness. This study aimed to estimate the spatial distribution of plant species richness using remote sensing in the Andes foothills of the Maule Region, Chile. This region has a secondary deciduous forest dominated by Nothofagus obliqua mixed with sclerophyll species. Floristic measurements were performed using a nested plot design with 60 plots of 225 m2 each. Multiple predictors were evaluated: 30 topographical and vegetation structure indexes from LiDAR data, and 32 spectral indexes and band transformations from the EO1-Hyperion sensor. A random forest algorithm was used to identify relevant variables in richness prediction, and these variables were used in turn to obtain a final multiple linear regression predictive model (Adjusted R2 = 0.651; RSE = 3.69). An independent validation survey was performed with significant results (Adjusted R2 = 0.571, RMSE = 5.05). Selected variables were statistically significant: catchment slope, altitude, standard deviation of slope, average slope, Multiresolution Ridge Top Flatness index (MrRTF) and Digital Crown Height Model (DCM). The information provided by LiDAR delivered the best predictors, whereas hyperspectral data were discarded due to their low predictive power. |
| first_indexed | 2024-12-13T08:25:38Z |
| format | Article |
| id | doaj.art-54ad7051581247d9a90f4d3f3356310b |
| institution | Directory Open Access Journal |
| issn | 2072-4292 |
| language | English |
| last_indexed | 2024-12-13T08:25:38Z |
| publishDate | 2015-03-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Remote Sensing |
| spelling | doaj.art-54ad7051581247d9a90f4d3f3356310b2022-12-21T23:53:54ZengMDPI AGRemote Sensing2072-42922015-03-01732692271410.3390/rs70302692rs70302692Comparison of Airborne LiDAR and Satellite Hyperspectral Remote Sensing to Estimate Vascular Plant Richness in Deciduous Mediterranean Forests of Central ChileAndrés Ceballos0Jaime Hernández1Patricio Corvalán2Mauricio Galleguillos3Laboratory of Geomatics and Landscape Ecology, Forestry and Nature Conservation Faculty, University of Chile, Av. Santa Rosa 11315, La Pintana, Santiago, ChileLaboratory of Geomatics and Landscape Ecology, Forestry and Nature Conservation Faculty, University of Chile, Av. Santa Rosa 11315, La Pintana, Santiago, ChileLaboratory of Geomatics and Landscape Ecology, Forestry and Nature Conservation Faculty, University of Chile, Av. Santa Rosa 11315, La Pintana, Santiago, ChileLaboratory of Geomatics and Landscape Ecology, Forestry and Nature Conservation Faculty, University of Chile, Av. Santa Rosa 11315, La Pintana, Santiago, ChileThe Andes foothills of central Chile are characterized by high levels of floristic diversity in a scenario, which offers little protection by public protected areas. Knowledge of the spatial distribution of this diversity must be gained in order to aid in conservation management. Heterogeneous environmental conditions involve an important number of niches closely related to species richness. Remote sensing information derived from satellite hyperspectral and airborne Light Detection and Ranging (LiDAR) data can be used as proxies to generate a spatial prediction of vascular plant richness. This study aimed to estimate the spatial distribution of plant species richness using remote sensing in the Andes foothills of the Maule Region, Chile. This region has a secondary deciduous forest dominated by Nothofagus obliqua mixed with sclerophyll species. Floristic measurements were performed using a nested plot design with 60 plots of 225 m2 each. Multiple predictors were evaluated: 30 topographical and vegetation structure indexes from LiDAR data, and 32 spectral indexes and band transformations from the EO1-Hyperion sensor. A random forest algorithm was used to identify relevant variables in richness prediction, and these variables were used in turn to obtain a final multiple linear regression predictive model (Adjusted R2 = 0.651; RSE = 3.69). An independent validation survey was performed with significant results (Adjusted R2 = 0.571, RMSE = 5.05). Selected variables were statistically significant: catchment slope, altitude, standard deviation of slope, average slope, Multiresolution Ridge Top Flatness index (MrRTF) and Digital Crown Height Model (DCM). The information provided by LiDAR delivered the best predictors, whereas hyperspectral data were discarded due to their low predictive power.http://www.mdpi.com/2072-4292/7/3/2692florarichnessEO-1 Hyperionairborne LiDARpredictionAndes foothills |
| spellingShingle | Andrés Ceballos Jaime Hernández Patricio Corvalán Mauricio Galleguillos Comparison of Airborne LiDAR and Satellite Hyperspectral Remote Sensing to Estimate Vascular Plant Richness in Deciduous Mediterranean Forests of Central Chile Remote Sensing flora richness EO-1 Hyperion airborne LiDAR prediction Andes foothills |
| title | Comparison of Airborne LiDAR and Satellite Hyperspectral Remote Sensing to Estimate Vascular Plant Richness in Deciduous Mediterranean Forests of Central Chile |
| title_full | Comparison of Airborne LiDAR and Satellite Hyperspectral Remote Sensing to Estimate Vascular Plant Richness in Deciduous Mediterranean Forests of Central Chile |
| title_fullStr | Comparison of Airborne LiDAR and Satellite Hyperspectral Remote Sensing to Estimate Vascular Plant Richness in Deciduous Mediterranean Forests of Central Chile |
| title_full_unstemmed | Comparison of Airborne LiDAR and Satellite Hyperspectral Remote Sensing to Estimate Vascular Plant Richness in Deciduous Mediterranean Forests of Central Chile |
| title_short | Comparison of Airborne LiDAR and Satellite Hyperspectral Remote Sensing to Estimate Vascular Plant Richness in Deciduous Mediterranean Forests of Central Chile |
| title_sort | comparison of airborne lidar and satellite hyperspectral remote sensing to estimate vascular plant richness in deciduous mediterranean forests of central chile |
| topic | flora richness EO-1 Hyperion airborne LiDAR prediction Andes foothills |
| url | http://www.mdpi.com/2072-4292/7/3/2692 |
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