scholarly journals Toward high‐resolution agronomic soil information and management zones delineated by ground‐based electromagnetic induction and aerial drone data

2021 ◽  
Author(s):  
Christian Hebel ◽  
Sophie Reynaert ◽  
Klaas Pauly ◽  
Pieter Janssens ◽  
Isabelle Piccard ◽  
...  
Keyword(s):  
High Resolution ◽  
Electromagnetic Induction ◽  
Management Zones ◽  
Soil Information

The delineation of agricultural management zones with high resolution remotely sensed data

2009 ◽  
Vol 10 (6) ◽  
pp. 471-487 ◽  
Author(s):  
Xiaoyu Song ◽  
Jihua Wang ◽  
Wenjiang Huang ◽  
Liangyun Liu ◽  
Guangjian Yan ◽  
...  
Keyword(s):  
High Resolution ◽  
Remotely Sensed ◽  
Agricultural Management ◽  
Remotely Sensed Data ◽  
Management Zones

Impact of regional climate model input and soil map resolution on projected winter wheat production in SW Germany

2020 ◽  
Author(s):  
Sebastian Gayler ◽  
Rajina Bajracharya ◽  
Tobias Weber ◽  
Thilo Streck
Keyword(s):  
High Resolution ◽  
Climate Model ◽  
Regional Climate ◽  
Regional Scale ◽  
Grid Cell ◽  
Small Scale ◽  
Climate Projections ◽  
Soil Map ◽  
Soil Information ◽  
The Impact

<p>Agricultural ecosystem models, driven by climate projections and fed with soil information and plausible management scenarios are frequently used tools to predict future developments in agricultural landscapes. On the regional scale, the required soil parameters must be derived from soil maps that are available in different spatial resolutions, ranging from grid cell sizes of 50 m up to 1 km and more. The typical spatial resolution of regional climate projections is currently around 12 km. Given the small-scale heterogeneity in soil properties, using the most accurate soil representation could be important for predictions of crop growth. However, simulations with very highly resolved soil data requires greater computing time and higher effort for data organization and storage. Moreover, the higher resolution may not necessarily lead to better simulations due to redundant information of the land surface and because the impact of climate forcing could dominate over the effect of soil variability. This leads to the question if the use of high-resolution soil data leads to significantly different predictions of future yields and grain protein trends compared to simulations in which soil data is adapted to the resolution of the climate input.</p><p>This study investigated the impact of weather and soil input on simulated crop growth in an intensively used agricultural region in Southwest Germany. For all areas classified as ‘arable land’ (CLC10), winter wheat growth was simulated over a 44-year period (2006 to 2050) using weather projections from three regional climate models and soil information at two spatial resolutions. The simulations were performed with the model system Expert-N 5.0, where the crop model Gecros was combined with the Richards equation and the CN turnover module of the model Daisy. Soil hydraulic parameters as well as initial values of soil organic matter pools were estimated from BK50 soil map information on soil texture and soil organic matter content, using pedo-transfer functions and SOM pool fractionation following Bruun and Jensen (2002). The coarser soil map is derived from BK50 soil map (50m x 50m) by selecting only the dominant soil type in a 12km × 12km grid to be representative for that grid cell. The crop model was calibrated with field data of crop phenology, leaf area, biomass, yield and crop nitrogen, which were collected at a research station within the study area between 2009 and 2018.</p><p>The predicted increase in temperatures during the growing season correlated with earlier maturity, lower yields and a higher grain protein content. The regional mean values varied by +/- 0.5 t/ha or +/-0.3 percentage points of protein content depending to the climate model used. On the regional scale, the simulated trends remained unchanged using high-resolution or coarse resolution soil data. However, there are strong differences in both the forecasted averages and the distribution of forecasts, as the coarser resolution captures neither the small-scale heterogeneity nor the average of the high-resolution results.</p>

Detection of soil pipe network by electromagnetic induction (EMI) in relation to the high resolution UAV data

2021 ◽  
Author(s):  
Anita Bernatek-Jakiel ◽  
Marta Kondracka ◽  
Maciej Liro
Keyword(s):  
Electrical Conductivity ◽  
High Resolution ◽  
Electromagnetic Induction ◽  
Geophysical Methods ◽  
Ground Surface ◽  
Degradation Process ◽  
Receiver Coil ◽  
Small Catchment ◽  
Eastern Carpathians ◽  
Soil Piping

<p>Subsurface erosion by soil piping is a widespread land degradation process that occurs in different soil types around the world. Recent studies have shown that piping erosion may lead to the significant soil loss and disturbances of ground surface. This process accelerates also gully erosion. However, it is still omitted in hydrological models of a catchment, as well as in soil and water erosion models. It seems that the main problem in soil piping studies lies on the basic issue, i.e., the detection of subsurface tunnels (soil pipes). As geophysical methods enable the exploration below the ground surface, they are promising in soil piping studies.</p><p> </p><p>This study aims to evaluate the suitability of the electromagnetic induction (EMI) to detect subsurface network of soil pipes. The detailed study was conducted in the small catchment (Cisowiec) in the Bieszczady Mts. (the Eastern Carpathians, SE Poland), where pipes develop in Cambisols. The measurements were carried out using a conductivity meter EM38-MK2 (Geonics) in both vertical and horizontal measuring dipole orientations. The EM38-MK2 provided simultaneous measurements of apparent electrical conductivity with two transmitter receiver coil separation (0.5 m and 1 m). In order to compare subsurface data with the surface response (i.e., depressions and collapses), the high resolution DEM and orthophotos have been produced. These data have been prepared using Structure from Motion (SfM) technique based on the images taken from the low altitude by an Unmanned Aerial Vehicle (UAV; DJI Phantom-4 equipped with a 1' camera). The UAV-derived products (orthophotos and DEM) have the resolution of 0.014 x 0.014 m and point density of 9240 per 1 m<sup>2</sup>.</p><p> </p><p>The EMI results are presented on the maps that gathered data at three depths (0.4 m, 0.75 m, 1.5 m). The results revealed the soil pipes as areas characterized by higher electrical conductivity than the surroundings. The spatial distribution of subsurface tunnels corresponds with the ground depressions and collapses detected in the field and seen on the high resolution DEM and orthophoto. The use of EMI in piping research has been evaluated.</p><p> </p><p>The study is supported by the National Science Centre, Poland within the first author’s project SONATINA 1 (2017/24/C/ST10/00114).</p>

scholarly journals Mapping Soil Properties to Advance the State of Spatial Soil Information for Greater Food Security on US Tribal Lands

2021 ◽  
Vol 1 ◽  
Author(s):  
Bryan Fuentes ◽  
Amanda J. Ashworth ◽  
Mercy Ngunjiri ◽  
Phillip Owens
Keyword(s):  
Food Security ◽  
High Resolution ◽  
Soil Properties ◽  
Cation Exchange ◽  
Cation Exchange Capacity ◽  
Soil Property ◽  
Exchange Capacity ◽  
Soil Survey ◽  
Soil Information ◽  
Tribal Lands

Knowledge, data, and understanding of soils is key for advancing agriculture and society. There is currently a critical need for sustainable soil management tools for enhanced food security on Native American Tribal Lands. Tribal Reservations have basic soil information and limited access to conservation programs provided to other U.S producers. The objective of this study was to create first ever high-resolution digital soil property maps of Quapaw Tribal Lands with limited data for sustainable soil resource management. We used a digital soil mapping (DSM) approach based on fuzzy logic to model the spatial distribution of 24 soil properties at 0–15 and 15–30 cm depths. A digital elevation model with 3 m resolution was used to derive terrain variables and a total of 28 samples were collected at 0–30 cm over the 22,880-ha reservation. Additionally, soil property maps were derived from Gridded Soil Survey Geographic Database (gSSURGO) for comparison. When comparing properties modeled by DSM to those derived from gSSURGO, DSM resulted in lower root mean squared error (RMSE) for percent clay and sand at 0–15 cm, and cation exchange capacity, percent clay, and pH at 15–30 cm. Conversely, gSSURGO-derived maps resulted in lower RMSE for cation exchange capacity, pH, and percent silt at the 0–15 cm depth, and percent sand and silt at the 15–30 cm depth. Although, some of the soil properties derived from gSSURGO had lower RMSE, spatial soil property patterns modeled by DSM were in better agreement with the topographic complexity and expected soil-landscape relationships. The proposed DSM approach developed property maps at high-resolution, which sets the baseline for production of new spatial soil information for Quapaw Tribal soils. It is expected that these maps and future versions will be useful for soil, crop, and land-use decisions at the farm and Tribal-level for increased agricultural productivity and economic development. Overall, this study provides a framework for developing DSM on Tribal Lands for improving the accuracy and detail of soil property maps (relative to off the shelf products such as SSURGO) that better represents soil-forming environments and the spatial variability of soil properties on Tribal Lands.

Urban soil exploration through multi-receiver electromagnetic induction and stepped-frequency ground penetrating radar

2015 ◽  
Vol 17 (7) ◽  
pp. 1271-1281 ◽  
Author(s):  
Ellen Van De Vijver ◽  
Marc Van Meirvenne ◽  
Laura Vandenhaute ◽  
Samuël Delefortrie ◽  
Philippe De Smedt ◽  
...  
Keyword(s):  
High Resolution ◽  
Ground Penetrating Radar ◽  
Urban Soil ◽  
Electromagnetic Induction ◽  
State Of The Art ◽  
Anthropogenic Disturbances ◽  
Soil Exploration ◽  
Stepped Frequency ◽  
Ground Penetrating

A high-resolution survey with two state-of-the-art geophysical sensors was performed to investigate an urban soil including various anthropogenic disturbances.

scholarly journals Developing high resolution National Soil Information Grids of China

2021 ◽  
Author(s):  
Feng Liu ◽  
Huayong Wu ◽  
Yuguo Zhao ◽  
Decheng Li ◽  
Jin-Ling Yang ◽  
...  
Keyword(s):  
High Resolution ◽  
Soil Information
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