University of California, Santa Barbara-ko ikertzaileekin lankidetzan egindako argitalpenak (10)

2024

  1. Improving Fire Severity Analysis in Mediterranean Environments: A Comparative Study of eeMETRIC and SSEBop Landsat-Based Evapotranspiration Models

    Remote Sensing, Vol. 16, Núm. 2

  2. Next-gen regional fire risk mapping: Integrating hyperspectral imagery and National Forest Inventory data to identify hot-spot wildland-urban interfaces

    Science of the Total Environment, Vol. 940

2020

  1. Can landsat-derived variables related to energy balance improve understanding of burn severity from current operational techniques?

    Remote Sensing, Vol. 12, Núm. 5

  2. Enhanced burn severity estimation using fine resolution ET and MESMA fraction images with machine learning algorithm

    Remote Sensing of Environment, Vol. 244

2019

  1. Burn severity analysis in Mediterranean forests using maximum entropy model trained with EO-1 Hyperion and LiDAR data

    ISPRS Journal of Photogrammetry and Remote Sensing, Vol. 155, pp. 102-118

  2. Vegetation and soil fire damage analysis based on species distribution modeling trained with multispectral satellite data

    Remote Sensing, Vol. 11, Núm. 15

2017

  1. Burn severity mapping from Landsat MESMA fraction images and Land Surface Temperature

    Remote Sensing of Environment, Vol. 190, pp. 83-95

2016

  1. Burn severity influence on post-fire vegetation cover resilience from Landsat MESMA fraction images time series in Mediterranean forest ecosystems

    Remote Sensing of Environment, Vol. 184, pp. 112-123

2013

  1. Multiple Endmember Spectral Mixture Analysis (MESMA) to map burn severity levels from Landsat images in Mediterranean countries

    Remote Sensing of Environment, Vol. 136, pp. 76-88

2012

  1. Evaluation of potential of multiple endmember spectral mixture analysis (MESMA) for surface coal mining affected area mapping in different world forest ecosystems

    Remote Sensing of Environment, Vol. 127, pp. 181-193