Blending Landsat and MODIS Data to Generate Multispectral Indices: A Comparison of “Index-then-Blend” and “Blend-then-Index” Approaches
about
Combining HJ CCD, GF-1 WFV and MODIS Data to Generate Daily High Spatial Resolution Synthetic Data for Environmental Process Monitoring.Crop Phenology Detection Using High Spatio-Temporal Resolution Data Fused from SPOT5 and MODIS Products.Object-Based Paddy Rice Mapping Using HJ-1A/B Data and Temporal Features Extracted from Time Series MODIS NDVI DataHigh Resolution Mapping of Cropping Cycles by Fusion of Landsat and MODIS DataA generalization of spatial and temporal fusion methods for remotely sensed surface parametersAn Improved Method for Producing High Spatial-Resolution NDVI Time Series Datasets with Multi-Temporal MODIS NDVI Data and Landsat TM/ETM+ Images
P2860
Blending Landsat and MODIS Data to Generate Multispectral Indices: A Comparison of “Index-then-Blend” and “Blend-then-Index” Approaches
description
wetenschappelijk artikel
@nl
наукова стаття, опублікована у вересні 2014
@uk
name
Blending Landsat and MODIS Dat ...... “Blend-then-Index” Approaches
@en
Blending Landsat and MODIS Dat ...... “Blend-then-Index” Approaches
@nl
type
label
Blending Landsat and MODIS Dat ...... “Blend-then-Index” Approaches
@en
Blending Landsat and MODIS Dat ...... “Blend-then-Index” Approaches
@nl
prefLabel
Blending Landsat and MODIS Dat ...... “Blend-then-Index” Approaches
@en
Blending Landsat and MODIS Dat ...... “Blend-then-Index” Approaches
@nl
P2093
P2860
P50
P356
P1433
P1476
Blending Landsat and MODIS Dat ...... “Blend-then-Index” Approaches
@en
P2093
Abdollah Jarihani
Irina Emelyanova
Thomas Van Niel
P2860
P304
P356
10.3390/RS6109213
P577
2014-09-26T00:00:00Z