Geospatial solutions for evaluating the impact of the Tigray conflict on farming

Demissie, Biadgilgn; Nyssen, Jan; Annys, Sofie; Negash, Emnet; Gebrehiwet, Tesfakiros; Abay, Fetien; Wolff, Éléonore

doi:10.1007/s11600-022-00779-7

Cited by 12 publications

(12 citation statements)

References 35 publications

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“…The soil fraction is lowest in the period from when plants are tallest (green material covers the soil) to when they are then harvested (crop residue covers) the soil. Soil fraction then progressively increases due to weathering and plowing through the spring, peaking in the March-May timeframe (Demissie et al 2022). NPV is lowest when crops are most photosynthetic (June-September), peaks in late fall due to crop residue on the soil surface, then slowly declines due to weathering and plowing.…”

Section: Revised Methods Resultsmentioning

confidence: 99%

“…However, conflicts make it unsafe to assess agricultural activity in person (Witmer 2008, Eklund et al 2017, Demissie et al 2022. Monitoring agricultural activity during conflicts is particularly important because agriculture (particularly smallholder farming) may be affected by conflict activities, primarily through cropland abandonment (Baumann et al 2015, Eklund et al 2017, Olsen et al 2021, Kemmerling et al 2022, Li et al 2022.…”

Section: Introductionmentioning

confidence: 99%

“…A particular concern in conflict areas is that, if rainfall is sufficient, abandoned fields can green up with weeds, mimicking that they were planted with a food crop (Witmer 2008, Demissie et al 2022. Abandoned fields are different from actively fallowed fields, where the land is managed in an effort to restore available nutrients, including plowing and the planting of cover crops (Kraaijvanger andVeldkamp 2015, Nyssen et al 2022).…”

Section: Introductionmentioning

confidence: 99%

“…Determining species differences of crops and weeds is not possible with multispectral data, so proxies relating to field preparation are necessary to disentangle the weed/crop planting issue. For instance, under non-conflict circumstances, crop areas in Tigray, Ethiopia are plowed two to six times prior to planting to exhaust the soil weed seed bank and increase the potential for rainfall infiltration/decrease runoff (Aune et al 2001, Nyssen et al 2019, Demissie et al 2022. Therefore, croplands may be identified by the seasonal presence of soil exposure (Witmer 2008, Yin et al 2020, Demissie et al 2022.…”

Section: Introductionmentioning

confidence: 99%

“…For instance, under non-conflict circumstances, crop areas in Tigray, Ethiopia are plowed two to six times prior to planting to exhaust the soil weed seed bank and increase the potential for rainfall infiltration/decrease runoff (Aune et al 2001, Nyssen et al 2019, Demissie et al 2022. Therefore, croplands may be identified by the seasonal presence of soil exposure (Witmer 2008, Yin et al 2020, Demissie et al 2022. The absence of plowing results in brighter pixels in comparison to the same month of a pre-conflict year, as plowing breaks up the flat, bright soil surface crust, exposing damp soil that is naturally darker and may have shadows from furrows, further darkening a plowed field (Nyssen et al 2022).…”

Section: Introductionmentioning

confidence: 99%

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Crop area change in the context of civil war in Tigray, Ethiopia

Peterson,

Husak,

Shukla

et al. 2024

Environ. Res.: Food Syst.

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Smallholder, rain-fed agriculture has been practiced in Tigray, Ethiopia for thousands of years, so farmers have experience with natural disturbances. However, civil war began in November 2020 and disrupted the agricultural system through theft and destruction of farming implements, livestock, and crops, and threats towards human activity, impacting farmers’ ability to work their land. To investigate effects on agricultural activity we used remote sensing data and machine learning methods to map cropped area across Tigray from 2017-2022. Specifically, spectral mixture analysis was applied to Sentinel-2 data to produce green vegetation, non-photosynthetic vegetation, soil, and shade endmember fractions. Monthly medians of these fractions, along with reference data generated by manual interpretation of very high spatial resolution data, were used to drive random forests-based classifications of crop/no-crop for each year. Initially we used a greenness threshold to distinguish between active and abandoned fields for a given year, but when rainfall is adequate, fields abandoned due to conflict can green up with weeds rather than crops, leading to false positive crop detections. In the spring, abandoned fields have a bright soil crust due to a lack of plowing, so these fields were removed from the crop reference data if the March soil endmember fraction anomaly was greater than 0.15. Overall accuracies of the crop/no-crop maps ranged from 80-90% for the different districts. Producer’s/user’s accuracies for the crop class ranged from 55-80%/69-90%. In 2021, crop area declined by 29% and 20% in West and Northwest Tigray, respectively, corresponding with reports of intense conflict there. The rest of Tigray showed a mix of smaller increases and decreases, indicating more resilience to the regional conflict. Finally, in 2022 we found increases in cropped area relative to 2021, for all districts except West Tigray, indicating recovery except for the areas where conflict was most severe.

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Section: Revised Methods Resultsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 3 more Smart Citations

Crop area change in the context of civil war in Tigray, Ethiopia

Peterson,

Husak,

Shukla

et al. 2024

Environ. Res.: Food Syst.

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Dryland Social-Ecological Systems in Africa

Li,

Diop,

Hirwa

et al. 2024

Dryland Social-Ecological Systems in Changing Environments

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In Africa, dryland ecosystem is the largest biome complex, covering 60% of the continent and home to ~525 million people. Coupled with adverse climatic conditions and anthropogenic pressures make dryland highly vulnerable to environmental degradation. In this chapter, we elucidate an overview of dryland socio-ecological systems (DSES) in Africa. We examine dryland biodiversity as a basis for ecosystem services in Africa. Therefore, we investigate the research and technology gaps in African drylands. Finally, we conclude and highlight the future perspectives for sustainable DSES management. Sustainable development requires an understanding of and adherence to the proper functioning of DSES. We recommend to promote sustainable agricultural best practices and innovations as a tool to enhance community resilience and cope with climate change impacts on food security, use modern observational data and develop idealistic models to better understand the climate-drylands-food security nexus approaches, and strengthen dryland research and management effectiveness through emerging and affordable technologies.

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