Header

UZH-Logo

Maintenance Infos

Spatial differentiation of arable land and permanent grassland to improve a land management model for nutrient balancing


Gomez Giménez, Marta; Della Peruta, Raniero; de Jong, Rogier; Keller, Armin; Schaepman, Michael E (2016). Spatial differentiation of arable land and permanent grassland to improve a land management model for nutrient balancing. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 9(12):5655-5665.

Abstract

Agroecosystems play an important role in providing economic and ecosystem services, which directly impact society. Inappropriate land use and unsustainable agricultural management with associated nutrient cycles can jeopardize important soil functions such as food production, livestock feeding, and conservation of biodiversity. The objective of this study was to integrate remotely sensed land cover information into a regional land management model (LMM) to improve the assessment of spatially explicit nutrient balances for agroecosystems. Remotely sensed data and an optimized parameter set contributed to an improved LMM output, allowing for a better land allocation within the model. The best input parameter combination was based on two different land cover classifications with overall accuracies of 98%, improving the land allocation performance compared with using nonspatially explicit input. We conclude that the combined use of remote sensing data and the LMM has the potential to provide valuable guidance for farm practices. It further helps to generate a spatial description of farm-level nutrient balance, a crucial ability when choosing policy options related to sustainable management of agricultural soils.

Abstract

Agroecosystems play an important role in providing economic and ecosystem services, which directly impact society. Inappropriate land use and unsustainable agricultural management with associated nutrient cycles can jeopardize important soil functions such as food production, livestock feeding, and conservation of biodiversity. The objective of this study was to integrate remotely sensed land cover information into a regional land management model (LMM) to improve the assessment of spatially explicit nutrient balances for agroecosystems. Remotely sensed data and an optimized parameter set contributed to an improved LMM output, allowing for a better land allocation within the model. The best input parameter combination was based on two different land cover classifications with overall accuracies of 98%, improving the land allocation performance compared with using nonspatially explicit input. We conclude that the combined use of remote sensing data and the LMM has the potential to provide valuable guidance for farm practices. It further helps to generate a spatial description of farm-level nutrient balance, a crucial ability when choosing policy options related to sustainable management of agricultural soils.

Statistics

Citations

1 citation in Web of Science®
1 citation in Scopus®
Google Scholar™

Altmetrics

Downloads

3 downloads since deposited on 02 Nov 2016
2 downloads since 12 months
Detailed statistics

Additional indexing

Item Type:Journal Article, refereed, original work
Communities & Collections:07 Faculty of Science > Institute of Geography
Dewey Decimal Classification:910 Geography & travel
Language:English
Date:2016
Deposited On:02 Nov 2016 10:06
Last Modified:08 Dec 2017 20:40
Publisher:Institute of Electrical and Electronics Engineers
ISSN:1939-1404
Publisher DOI:https://doi.org/10.1109/jstars.2016.2551729

Download