Remotely sensed characterization of forest fuel types by using satellite ASTER data
暂无分享,去创建一个
[1] W. G. Morris. Photo inventory of fine logging slash. , 1970 .
[2] S. Muraro. Slash fuel inventories from 70-mm low-level photography , 1970 .
[3] F. Albini. Estimating Wildfire Behavior and Effects , 1976 .
[4] T. M. Lillesand,et al. Remote Sensing and Image Interpretation , 1980 .
[5] H. Anderson. Aids to Determining Fuel Models for Estimating Fire Behavior , 1982 .
[6] R. Burgan,et al. BEHAVE : Fire Behavior Prediction and Fuel Modeling System -- FUEL Subsystem , 1984 .
[7] Southeastern Forest Experiment Station. General technical report , 1985 .
[8] T. M. Lillesand,et al. Remote sensing and image interpretation. Second edition , 1987 .
[9] E. Chuvieco,et al. Application of remote sensing and geographic information systems to forest fire hazard mapping. , 1989 .
[10] R. Muñoz. Algunas observaciones para una sevicultura preventiva de incendios forestales , 1990 .
[11] J. Boardman,et al. Mapping target signatures via partial unmixing of AVIRIS data: in Summaries , 1995 .
[12] J. Boardman,et al. Leveraging the High Dimensionality of AVIRIS Data for improved Sub-Pixel Target i Unmixing and Rejection of False Positives : Mixture Tuned Matched Filtering , 1998 .
[13] E. Chuvieco,et al. Modeling forest fire danger from geographic information systems , 1998 .
[14] Russell G. Congalton,et al. Assessing the accuracy of remotely sensed data : principles and practices , 1998 .
[15] E. Chuvieco. Remote Sensing of Large Wildfires , 1999 .
[16] B. Oswald,et al. Classifying fuels with aerial photography in East Texas , 1999 .
[17] R. Keane,et al. Mapping vegetation and fuels for fire management on the Gila National Forest Complex, New Mexico , 2000 .
[18] R. Lasaponara,et al. Evaluation of a new satellite-based method for forest fire detection , 2001 .
[19] R. Keane,et al. Mapping wildland fuels for fire management across multiple scales: Integrating remote sensing, GIS, and biophysical modeling , 2001 .
[20] M. Vilà,et al. Positive fire–grass feedback in Mediterranean Basin woodlands , 2001 .
[21] Guobin Zhu,et al. Classification using ASTER data and SVM algorithms;: The case study of Beer Sheva, Israel , 2002 .
[22] D. Riaño,et al. Generation of fuel type maps from Landsat TM images and ancillary data in Mediterranean ecosystems , 2002 .
[23] Tiziana Simoniello,et al. A self-adaptive algorithm based on AVHRR multitemporal data analysis for small active fire detection , 2003 .
[24] Jan W. van Wagtendonk,et al. The use of multi-temporal Landsat Normalized Difference Vegetation Index (NDVI) data for mapping fuel models in Yosemite National Park, USA , 2003 .
[25] S. Reutebuch,et al. Estimating forest canopy fuel parameters using LIDAR data , 2005 .
[26] R. Lasaponara,et al. Inter‐comparison of AVHRR‐based fire susceptibility indicators for the Mediterranean ecosystems of southern Italy , 2005 .
[27] L. Telesca,et al. Discriminating dynamical patterns in burned and unburned vegetational covers by using SPOT‐VGT NDVI data , 2005 .
[28] R. Lasaponara,et al. Characterization and Mapping of Fuel Types for the Mediterranean Ecosystems of Pollino National Park in Southern Italy by Using Hyperspectral MIVIS Data , 2006 .
[29] J. Goldammer. Global Forest Resources Assessment 2005 – Thematic report on forest fires in the Central Asian Region and adjacent countries / FAO Fire Management Working Paper 16 , 2006 .
[30] R. Lasaponara,et al. Multiscale fuel type mapping in fragmented ecosystems: preliminary results from hyperspectral MIVIS and multispectral Landsat TM data , 2006 .
[31] L. Telesca,et al. Discrimination of Vegetational Patterns in Burned and Unburned Areas , 2006 .
[32] L. Telesca,et al. Fire‐induced variability in satellite SPOT‐VGT NDVI vegetational data , 2006 .
[33] L. Telesca,et al. Pre‐ and post‐fire behavioral trends revealed in satellite NDVI time series , 2006 .
[34] L. Telesca,et al. Vegetational patterns in burned and unburned areas investigated by using the detrended fluctuation analysis , 2006 .
[35] R. Lasaponara,et al. Multiscale fuel type characterization by using multisensor remote sensing data for the Mediterranean ecosystems of Southern Italy , 2006 .
[36] R. Lasaponara. Estimating spectral separability of satellite derived parameters for burned areas mapping in the Calabria region by using SPOT-Vegetation data , 2006 .
[37] A. Goetz,et al. Assessing spatial patterns of forest fuel using AVIRIS data , 2006 .