Evaluation of vegetation indices and apparent soil electrical conductivity for site-specific vineyard management in Chile

2016 ◽  
Vol 17 (4) ◽  
pp. 434-450 ◽  
Author(s):  
Rodrigo Ortega-Blu ◽  
Mauricio Molina-Roco
Keyword(s):  
Electrical Conductivity ◽  
Vegetation Indices ◽  
Soil Electrical Conductivity ◽  
Site Specific ◽  
Vineyard Management

scholarly journals Site-Specific Management Zones Based on Soil Electrical Conductivity in a Semiarid Cropping System

2003 ◽  
Vol 95 (2) ◽  
pp. 303 ◽  
Author(s):  
Cinthia K. Johnson ◽  
David A. Mortensen ◽  
Brian J. Wienhold ◽  
John F. Shanahan ◽  
John W. Doran
Keyword(s):  
Electrical Conductivity ◽  
Cropping System ◽  
Soil Electrical Conductivity ◽  
Site Specific ◽  
Management Zones ◽  
Specific Management

scholarly journals Low-Input Estimation of Site-Specific Lime Demand Based on Apparent Soil Electrical Conductivity and In Situ Determined Topsoil pH

Sensors ◽  
2019 ◽  
Vol 19 (23) ◽  
pp. 5280
Author(s):  
Moritz von Cossel ◽  
Harm Druecker ◽  
Eberhard Hartung
Keyword(s):  
Electrical Conductivity ◽  
Field Measurements ◽  
Ex Situ ◽  
Soil Electrical Conductivity ◽  
Standard Equipment ◽  
Site Specific ◽  
Input Estimation ◽  
Low Input ◽  
North Germany

Site-specific liming helps increase efficiency in agricultural production. For adequate determination of the lime demand, a combination of apparent soil electrical conductivity (ECa) and topsoil pH can be used. Here, it was hypothesized that this can also be done at low-input level. Field measurements using the EM38 MK I (Geonics, Canada) were conducted on three experimental sites in north Germany in 2011. The topsoil pH was measured based on two approaches: on the field using a handheld pH meter (Spectrum-Technologies Ltd., Bridgend, UK) with a flat electrode (in situ), and in the lab using standard equipment (ex situ). Both soil ECa (0.4–35.9 mS m−1) and pH (5.13–7.41) were heterogeneously distributed across the sites. The same was true of the lime demand (−1.35–4.18 Mg ha−1). There was a significant correlation between in situ and ex situ determined topsoil pH (r = 0.89; p < 0.0001). This correlation was further improved through non-linear regression (r = 0.92; p < 0.0001). Thus, in situ topsoil pH was found suitable for map-overlay with ECa to determine the site-specific lime demand. Consequently, the hypothesis could be confirmed: The combined use of data from EM38 and handheld pH meters is a promising low-input approach that may help implement site-specific liming in developing countries.

scholarly journals Site-Specific Management Zones Based on Soil Electrical Conductivity in a Semiarid Cropping System

2003 ◽  
Vol 95 (2) ◽  
pp. 303-315 ◽  
Author(s):  
Cinthia K. Johnson ◽  
David A. Mortensen ◽  
Brian J. Wienhold ◽  
John F. Shanahan ◽  
John W. Doran
Keyword(s):  
Electrical Conductivity ◽  
Cropping System ◽  
Soil Electrical Conductivity ◽  
Site Specific ◽  
Management Zones ◽  
Specific Management

Site-Specific Productivity Zones Delineated Using Bulk Soil Electrical Conductivity

2013 ◽  
Author(s):  
Newell R. Kitchen ◽  
Kenneth A. Sudduth ◽  
Brent Myers ◽  
Scott T. Drummond ◽  
Suk Young Hong
Keyword(s):  
Electrical Conductivity ◽  
Bulk Soil ◽  
Specific Productivity ◽  
Soil Electrical Conductivity ◽  
Site Specific

Analysis of Remote Sensing based Vegetation Indices (VIs) for Unmanned Aerial System (UAS): A Review

2020 ◽  
Vol 3 (2) ◽  
pp. 58-73
Author(s):  
Vijay Bhagat ◽  
Ajaykumar Kada ◽  
Suresh Kumar
Keyword(s):  
Remote Sensing ◽  
Spatial Data ◽  
Satellite Remote Sensing ◽  
Vegetation Indices ◽  
Unmanned Aerial System ◽  
Sustainable Land Management ◽  
Efficient Tool ◽  
Site Specific ◽  
The Earth ◽  
Interesting Area

Unmanned Aerial System (UAS) is an efficient tool to bridge the gap between high expensive satellite remote sensing, manned aerial surveys, and labors time consuming conventional fieldwork techniques of data collection. UAS can provide spatial data at very fine (up to a few mm) and desirable temporal resolution. Several studies have used vegetation indices (VIs) calculated from UAS based on optical- and MSS-datasets to model the parameters of biophysical units of the Earth surface. They have used different techniques of estimations, predictions and classifications. However, these results vary according to used datasets and techniques and appear very site-specific. These existing approaches aren’t optimal and applicable for all cases and need to be tested according to sensor category and different geophysical environmental conditions for global applications. UAS remote sensing is a challenging and interesting area of research for sustainable land management.

scholarly journals Spatial and Temporal Variability of Soil Salinity in the Yangtze River Estuary Using Electromagnetic Induction

2021 ◽  
Vol 13 (10) ◽  
pp. 1875
Author(s):  
Wenping Xie ◽  
Jingsong Yang ◽  
Rongjiang Yao ◽  
Xiangping Wang
Keyword(s):  
Electrical Conductivity ◽  
Spatial Distribution ◽  
Soil Salinity ◽  
Yangtze River ◽  
Laboratory Data ◽  
River Estuary ◽  
Yangtze River Estuary ◽  
Soil Electrical Conductivity ◽  
The Yangtze River ◽  
The Yangtze River Estuary

Soil salt-water dynamics in the Yangtze River Estuary (YRE) is complex and soil salinity is an obstacle to regional agricultural production and the ecological environment in the YRE. Runoff into the sea is reduced during the impoundment period as the result of the water-storing process of the Three Gorges Reservoir (TGR) in the upper reaches of the Yangtze River, which causes serious seawater intrusion. Soil salinity is a problem due to shallow and saline groundwater under serious seawater intrusion in the YRE. In this research, we focused on the temporal variation and spatial distribution characteristics of soil salinity in the YRE using geostatistics combined with proximally sensed information obtained by an electromagnetic induction (EM) survey method in typical years under the impoundment of the TGR. The EM survey with proximal sensing method was applied to perform soil salinity survey in field in the Yangtze River Estuary, allowing quick determination and quantitative assessment of spatial and temporal variation of soil salinity from 2006 to 2017. We developed regional soil salinity survey and mapping by coupling limited laboratory data with proximal sensed data obtained from EM. We interpreted the soil electrical conductivity by constructing a linear model between the apparent electrical conductivity data measured by an EM 38 device and the soil electrical conductivity (EC) of soil samples measured in laboratory. Then, soil electrical conductivity was converted to soil salt content (soil salinity g kg−1) through established linear regression model based on the laboratory data of soil salinity and soil EC. Semivariograms of regional soil salinity in the survey years were fitted and ordinary kriging interpolation was applied in interpolation and mapping of regional soil salinity. The cross-validation results showed that the prediction results were acceptable. The soil salinity distribution under different survey years was presented and the area of salt affected soil was calculated using geostatistics method. The results of spatial distribution of soil salinity showed that soil salinity near the riverbanks and coastlines was higher than that of inland. The spatial distribution of groundwater depth and salinity revealed that shallow groundwater and high groundwater salinity influenced the spatial distribution characteristics of soil salinity. Under long-term impoundment of the Three Gorges Reservoir, the variation of soil salinity in different hydrological years was analyzed. Results showed that the area affected by soil salinity gradually increased in different hydrological year types under the impoundment of the TGR.

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