Towards the identification and mapping of traditional agricultural landscapes at the national scale: an inventory approach from Italy

Soil Organic Carbon (SOC) plays a crucial role in agricultural ecosystems. However, its abundance is spatially variable at different scales. In recent years, machine learning (ML) algorithms have become an important tool in the spatial prediction of SOC at regional to continental scales. Particularly in agricultural landscapes, the prediction of SOC is a challenging task.In this study, our aim is to evaluate the capability of two ML algorithms (Random Forest and Boosted Regression Trees) for topsoil (0 to 30 cm) SOC prediction in soils under agricultural use at national scale for Germany. In order to build the models, 50 environmental covariates representing topography, climate factors, land use as well as soil properties were selected. The SOC data we used was from the German Agricultural Soil inventory (2947 sampling points). A nested 5-fold cross-validation was used for model tuning and evaluation. Hyperparameter tuning for both ML algorithms was done by differential evolution optimization.&#160;This approach allows exploring an extensive set of field data in combination with state of the art pedometric tools. With a strict validation scheme, the geospatial-model performance was assessed. Current results indicate that the spatial SOC variation is to a minor extent predictable with the considered covariate data (<30% explained variance). This may partly be explained by a non-steady state of SOC content in agricultural soils with environmental drivers. We discuss the challenges of geo-spatial modelling and the value of ML algorithms in pedometrics.

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Globalisation and Agricultural Landscapes

10.1017/cbo9780511844928 ◽

2009 ◽

Cited By ~ 23

Keyword(s):

Agricultural Landscapes

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Youth Violence Prevention: Research-Guided Programs on a National Scale

PsycEXTRA Dataset ◽

10.1037/e554382012-153 ◽

2008 ◽

Author(s):

Ron Slaby

Keyword(s):

Violence Prevention ◽

Youth Violence ◽

Prevention Research ◽

Youth Violence Prevention ◽

National Scale

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To the issue of water treatment by hydrocyclone on the systems of the combined irrigation

Melioration and Water Management ◽

10.32962/0235-2524-2019-2-21-25 ◽

2020 ◽

Vol 0 (2) ◽

pp. 21-25

Author(s):

Nikolay Dubenok ◽

Andrey Novikov ◽

Sergei Borodychev ◽

Maria Lamskova

Keyword(s):

Water Treatment ◽

Organic Compounds ◽

Irrigation Water ◽

Irrigation System ◽

Petroleum Products ◽

Cylindrical Part ◽

Agricultural Landscapes ◽

Treatment Unit ◽

Drain Pipe ◽

Irrigation Network

At the stage of water treatment for irrigation systems, the efficiency capture coarse and fine mechanical impurities, as well as oil products and organic compounds affects the reliability of the equipment of the irrigation network and the safety of energy exchange processes in irrigated agricultural landscapes. The violation of work irrigation system can cause disruptions in irrigation schedules of agricultural crops, crop shortages, degradation phenomena on the soil and ecological tension. For the combined irrigation system, a water treatment unit has been developed, representing a hydrocyclone apparatus with a pipe filter in the case. For the capacity of 250 m3/h the main geometrical dimensions of hydrocyclone have been calculated. To organize the capture petroleum products and organic compounds, it has been proposed a modernization of a hydrocyclone unit, consisting in dividing the cylindrical part of the apparatus into two section. The first is section is for input irrigation water, the second one is for additional drainage of clarified irrigation water after sorption purification by the filter, placed on the disk and installed coaxially with the drain pipe and the pipe filter.

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Spatial regularities between non-immigrant and immigrant numbers in Canada

MIGRATION LETTERS ◽

10.33182/ml.v11i1.171 ◽

2014 ◽

Vol 11 (1) ◽

pp. 90-100

Author(s):

Yigit Aydede

Keyword(s):

Fixed Effects ◽

Spatial Scales ◽

National Scale ◽

Pooled Data

The present study intends to reveal spatial regularities between non-immigrant and immigrant numbers in two different ways. First, it questions the existence of those regularities when spatial scales get finer. Second, it uses pooled data over four population censuses covering the period from 1991 to 2006, which enabled us to apply appropriate techniques to remove those unobserved fixed effects so that the estimations would accurately identify the linkage between local immigrant and non-immigrant numbers. The results provide evidence about the existence of negative spatial regularities between non-immigrant and immigrant numbers in Canada at national scale.

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