Evaluating Soil-Borne Causes of Biomass Variability in Grassland by Remote and Proximal Sensing
On a grassland field with sandy soils in Northeast Germany (Brandenburg), vegetation indices from multi-spectral UAV-based remote sensing were used to predict grassland biomass productivity. These data were combined with soil pH value and apparent electrical conductivity (ECa) from on-the-go proxima...
Main Authors: | Sebastian Vogel, Robin Gebbers, Marcel Oertel, Eckart Kramer |
---|---|
Format: | Article |
Language: | English |
Published: |
MDPI AG
2019-10-01
|
Series: | Sensors |
Subjects: | |
Online Access: | https://www.mdpi.com/1424-8220/19/20/4593 |
Similar Items
-
Low-Pass Filters for a Temperature Drift Correction Method for Electromagnetic Induction Systems
by: Martial Tazifor Tchantcho, et al.
Published: (2023-08-01) -
The Relationship between Soil Electrical Parameters and Compaction of Sandy Clay Loam Soil
by: Katarzyna Pentoś, et al.
Published: (2021-02-01) -
SOIL PROPERTIES MAPPING USING PROXIMAL AND REMOTE SENSING AS COVARIATE
by: Maiara Pusch, et al.
Published: (2021-12-01) -
Vertical Soil Profiling Using a Galvanic Contact Resistivity Scanning Approach
by: Luan Pan, et al.
Published: (2014-07-01) -
Soil pH Mapping with an On-The-Go Sensor
by: Jan Seidel, et al.
Published: (2011-01-01)