Remote sensing in food production  and #8211; a review

Calvão, Teresa; Pessoa, Maria Fernanda

doi:10.9755/ejfa.v27i2.19272

Cited by 9 publications

(4 citation statements)

References 77 publications

(160 reference statements)

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“…Freely available data of present and spatially explicit data on cultivated crop types are rare. Remote sensing data are a valuable source of present and former land use/land cover and therefore on cropland and crop types mapping (e.g., [53][54][55]). The 'Semi-Automated Classification' plug-in [56] for QGIS [57] provides a freely available implementation of classical supervised image classification approaches.…”

Section: Present Crop Types and Crop Rotationmentioning

confidence: 99%

Spatially Explicit Soil Compaction Risk Assessment of Arable Soils at Regional Scale: The SaSCiA-Model

et al. 2018

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Soil compaction caused by field traffic is one of the main threats to agricultural landscapes. Compacted soils have a reduced hydraulic conductivity, lower plant growth and increased surface runoff resulting in numerous environmental issues such as increased nutrient leaching and flood risk. Mitigating soil compaction, therefore, is a major goal for a sustainable agriculture and environmental protection. To prevent undesirable effects of field traffic, it is essential to know where and when soil compaction may occur. This study developed a model for soil compaction risk assessment of arable soils at regional scale. A combination of (i) soil, weather, crop type and machinery information; (ii) a soil moisture model and (iii) soil compaction models forms the SaSCiA-model (Spatially explicit Soil Compaction risk Assessment). The SaSCiA-model computes daily maps of soil compaction risk and associated area statistics for varying depths at actual field conditions and for entire regions. Applications with open access data in two different study areas in northern Germany demonstrated the model’s applicability. Soil compaction risks strongly varied in space and time throughout the year. SaSCiA allows a detailed spatio-temporal analysis of soil compaction risk at the regional scale, which exceed those of currently available models. Applying SaSCiA may support farmers, stakeholders and consultants in making decision for a more sustainable agriculture.

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Section: Present Crop Types and Crop Rotationmentioning

confidence: 99%

Spatially Explicit Soil Compaction Risk Assessment of Arable Soils at Regional Scale: The SaSCiA-Model

et al. 2018

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“…To monitor the yield of specific crops and the yield losses under the effects of flood risk, we combined remote sensing imagery and crop statistics to develop empirical regression-based yield models. More information on crop yield prediction by remote sensing can be referred to Atzberger (2013), Calvão & Pessoa (2015) and Xue & Su (2017). The comparison between vegetation indices from remote sensing imagery and the official yield statistics was carried out to derive regression models as follows:…”

Section: Crop Yield Model Developmentmentioning

confidence: 99%

Integrated remote sensing imagery and two-dimensional hydraulic modeling approach for impact evaluation of flood on crop yields

Chen

Liang

Liu

et al. 2017

Journal of Hydrology

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“…In recent years, locust management has achieved remarkable results in China. However, in locust areas (the area possessing suitable breeding habitat for locusts and has locust infestation) accurate extraction is not easy due to the migration of locusts and the influence of global warming and human activities [5,6]. Therefore, the aim of this study is to achieve the accurate extraction of large-scale locust areas, which is significant for locust ecological control and environmental protection.…”

Section: Introductionmentioning

confidence: 99%

A Landscape-Based Habitat Suitability Model (LHS Model) for Oriental Migratory Locust Area Extraction at Large Scales: A Case Study along the Middle and Lower Reaches of the Yellow River

et al. 2022

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The Oriental migratory locust is a destructive agricultural pest in China. Large-scale locust area (the area possessing suitable breeding habitat for locusts and has locust infestation) extraction and its evolution analysis are essential for locust ecological control. Existing methods seldom consider the spatial differences in the locust development and habitat landscape structures in large areas. To analyze these effects, our study proposed a landscape-based habitat suitability model (LHS model) for large-scale locust area extraction based on remote sensing data, taking the middle and lower reaches of the Yellow River (MLYR) as an example. Firstly, the DD model was used to simulate locust development and obtain habitat factors of the corresponding dates; secondly, the patch distribution of different land cover classes and their adjacent landscape characteristics were analyzed to determine the landscape-based factors memberships; finally, the habitat suitability index was calculated by combining the factors memberships and weights to extract the locust area. Compared with the patch-based model using moving windows (patch based-analytic hierarchy process model, R2 = 0.77), the LHS model accuracy improved significantly (R2 = 0.83). Our results showed that the LHS model has a better application prospect in large-scale locust area extraction. By analyzing the locust areas evolution along the MLYR extracted using the LHS model, we found human activities were the main factors affecting the locust areas evolution from 2016 to 2020, including: (1) planting the plants that locusts do not like and urbanization caused the decrease of the locust area; (2) the wetland protection policies may cause the increase of the locust area. The model and research results help locust control and prevention to realize the sustainable development of agriculture.

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Remote sensing in food production and #8211; a review

Cited by 9 publications

References 77 publications

Spatially Explicit Soil Compaction Risk Assessment of Arable Soils at Regional Scale: The SaSCiA-Model

Spatially Explicit Soil Compaction Risk Assessment of Arable Soils at Regional Scale: The SaSCiA-Model

Integrated remote sensing imagery and two-dimensional hydraulic modeling approach for impact evaluation of flood on crop yields

A Landscape-Based Habitat Suitability Model (LHS Model) for Oriental Migratory Locust Area Extraction at Large Scales: A Case Study along the Middle and Lower Reaches of the Yellow River

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