2 Results Found

Advanced Search

Select all

Results per page

Select all

Article

6 Citations

3,320 Views

22 Pages

Geostatistical Modelling of Soil Spatial Variability by Fusing Drone-Based Multispectral Data, Ground-Based Hyperspectral and Sample Data with Change of Support

Antonella Belmonte,
Carmela Riefolo,
Francesco Lovergine and
Annamaria Castrignanò

Remote Sens.2022, 14(21), 5442;https://doi.org/10.3390/rs14215442

29 October 2022

Traditional soil characterization methods are time consuming, laborious and invasive and do not allow for long-term repeatability of measurements. The overall aim of this paper was to assess and model spatial variability of the soil in an olive grove...

(This article belongs to the Special Issue Topsoil Characterization by Means of Remote Sensing)

Full Article

Article

2 Citations

3,841 Views

20 Pages

A Composite Method for Predicting Local Accuracies in Remotely Sensed Land-Cover Change Using Largely Non-Collocated Sample Data

Yingying Mei,
Jingxiong Zhang,
Wangle Zhang and
Fengzhu Liu

Remote Sens.2019, 11(23), 2818;https://doi.org/10.3390/rs11232818

28 November 2019

As in conventional error matrix-based accuracy assessments, collocated reference sample data are often used for characterizing per-pixel (local) accuracies in land-cover change maps so that local accuracy predictions can be made using direct methods....

Full Article