Land use optimization tool for sustainable intensification of high-latitude agricultural systems

Peltonen‐Sainio, Pirjo; Jauhiainen, Lauri; Laurila, Heikki; Sorvali, Jaana; Honkavaara, Eija; Wittke, Samantha; Karjalainen, Mika; Puttonen, Eetu

doi:10.1016/j.landusepol.2019.104104

Cited by 42 publications

(24 citation statements)

References 40 publications

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“…The Sentinel-2 data were processed automatically by utilizing the Earth Observation processing toolkit developed at the Finnish Geospatial Institute (FGI) (for more details see [26]). Cloud masks and NDVI-images were calculated by FGI by using ESA's Sentinel Application Platform python interface snappy3 [17,24].…”

Section: Methodsmentioning

confidence: 99%

“…The land use optimization tool freely available for all Finnish farmers was developed to support farmer's decision making on land allocation for sustainable intensification, extensification and afforestation [17] with the main emphasis on safeguarding environmental, economic and social sustainability in the long-run through land use changes, and overall guiding farmers towards more heterogeneous and flexible land use in space and time. Poorly performing fields that were identified in this study are likely to be an economic burden for farmers [42] if used for food production.…”

Section: Allocation Of Poorly Performing Fields-is Sustainability Conmentioning

confidence: 99%

“…Land use optimization is a means of allocating land in a rational way to improve resource use efficiency and to link the reduction of the environmental footprint to economic and social sustainability. The Natural Resources Institute Finland (Luke) has developed a land use optimization tool which is available for all the Finnish farmers at Luke's EconomyDoctor-portal [17]. Using the tool, field parcels with a high production capacity and valuable field parcel characteristics can be allocated for sustainable intensification, while underperforming parcels with poor physical characteristics can be allocated for extensification, or in the uttermost case for afforestation if there is no future food security role.…”

Section: Introductionmentioning

confidence: 99%

“…Using the tool, field parcels with a high production capacity and valuable field parcel characteristics can be allocated for sustainable intensification, while underperforming parcels with poor physical characteristics can be allocated for extensification, or in the uttermost case for afforestation if there is no future food security role. Thereby, farmers have access to a land use action plan to sustain climate-and resource-smart production [17] and to also follow other practices and principles of sustainable intensification [5,18].…”

Section: Introductionmentioning

confidence: 99%

“…To support land use optimization for farmers, a method for the estimation of productivity gaps was developed on the field parcel scale, based on Sentinel-2 derived Normalized Difference Vegetation Index (NDVI) values [17]. This study aimed to identify how farming system characteristics and farm and field parcel properties contribute to the risk of high NDVI-gaps.…”

Section: Introductionmentioning

confidence: 99%

See 4 more Smart Citations

Risk of Low Productivity is Dependent on Farm Characteristics: How to Turn Poor Performance into an Advantage

Peltonen‐Sainio

Jauhiainen

2019

Sustainability

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The principle role of agriculture is to produce food for the increasing human population. However, the environmental footprint needs to be simultaneously reduced. Data from the Finnish Food Authority (181,108 parcels in the south-western crop production region of Finland) were used to identify the farming system, farm type, farm size, field parcel scale, physical parcel characteristics, cultivated crops, crop rotations and cultivars. Sentinel-2 derived Normalized Difference Vegetation Index (NDVI) values were used to identify fields with very low productivity. Thereby, the impacts of farm and field characteristics on risks of low NDVI values and their associated means of coping by the farmer were studied. High variations in field parcel characteristics and growth capacity were typical in the studied area. Although it is challenging for farmers, high variation can provide many opportunities for the development of multifunctional and resource-smart production systems, e.g., by optimizing land use: allocating high-quality fields for food production, and poorly performing fields for extensification, i.e., the production of environmental benefits. Many usable policy instruments are available to support such a transition, but more focus should be put onto the most efficient means to enable progress towards environmentally, economically and socially sustainable high-latitude agricultural systems.

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Section: Methodsmentioning

confidence: 99%

Section: Allocation Of Poorly Performing Fields-is Sustainability Conmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 3 more Smart Citations

Risk of Low Productivity is Dependent on Farm Characteristics: How to Turn Poor Performance into an Advantage

Peltonen‐Sainio

Jauhiainen

2019

Sustainability

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Within‐field variation of crop yield loss from cover crops

Girz,

Mattila

2024

Agronomy Journal

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The amount of high‐resolution agricultural data has increased rapidly in the current decade. Integration of satellite multispectral imagery, combine harvester yield monitoring data, and soil moisture mapping allows managing for within‐field variation and better interpreting on‐farm experimentation. In this study, we investigated the effect of cover crops on yield in Finland by integrating Sentinel‐2 satellite imagery (normalized difference vegetation index), topographic soil moisture indexes, and high‐resolution yield data. The experiment was run by three farmers over 4 years and serves as an example for low‐cost on‐farm experimentation. Our results confirmed earlier findings that undersown cover crops result in approximately 5% yield loss. We also found that the effect is highly variable across farms and within fields. The highest yield losses were found in areas of the field, which were wetter in the spring seeding time. The competition between crop and cover crop could be observed in the vegetation maps for autumn and early summer. Combining NDVI and soil moisture maps allows delineating field zones, which require extra management to reduce the risk of yield loss from cover crop resource competition. Evaluating the overall effect of cover crops on yield would require replication on more farms. The within‐field variation results and workflow investigated in this study can guide placement of sampling areas within those fields.

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Toward potential area identification for land consolidation and ecological restoration: an integrated framework via land use optimization

Yang

Chen

2022

Environ Dev Sustain

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Land use optimization tool for sustainable intensification of high-latitude agricultural systems

Cited by 42 publications

References 40 publications

Risk of Low Productivity is Dependent on Farm Characteristics: How to Turn Poor Performance into an Advantage

Risk of Low Productivity is Dependent on Farm Characteristics: How to Turn Poor Performance into an Advantage

Within‐field variation of crop yield loss from cover crops

Toward potential area identification for land consolidation and ecological restoration: an integrated framework via land use optimization

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