The forgotten land use class: Mapping of fallow fields across the Sahel using Sentinel-2

REMOTE SENSING OF ENVIRONMENT

卷:239

Article

Tong, Xiaoye^1,2  Brandt, Martin¹  Hiernaux, Pierre³  Herrmann, Stefanie⁴  Rasmussen, Laura Yang^1,5  Rasmussen, Kjeld¹  Tian, Feng⁶  Tagesson, Torbern^1,6  Zhang, Wenmin⁷  Fensholt, Rasmus¹ 

[1] Univ Copenhagen, Dept Geosci & Nat Resource Management IGN, DK-1350 Copenhagen, Denmark

[2] DHI GRAS, Agern Alle 5, DK-2970 Horsholm, Denmark

[3] Pastoc, 30 Chemin Jouanal, F-82160 Caylus, France

[4] Univ Arizona, Tucson, AZ 85719 USA

[5] Univ British Columbia, Dept Forest & Conservat Sci, 3609-2424 Main Mall, Vancouver, BC V6T 1Z4, Canada

[6] Lund Univ, Dept Phys Geog & Ecosyst Sci, Solvegatan 12, S-22362 Lund, Sweden

[7] Nanjing Normal Univ, Sch Geog Sci, Nanjing 210023, Peoples R China

关键词: Fallow fields;    Cropland;    Satellite image time series;    Land use/cover mapping;    Sentinel-2;    Drylands;    Sahel;   

DOI  :  10.1016/j.rse.2019.111598

来源: Elsevier

【 摘 要 】

Remote sensing-derived cropland products have depicted the location and extent of agricultural lands with an ever increasing accuracy. However, limited attention has been devoted to distinguishing between actively cropped fields and fallowed fields within agricultural lands, and in particular so in grass fallow systems of semi-arid areas. In the Sahel, one of the largest dryland regions worldwide, crop-fallow rotation practices are widely used for soil fertility regeneration. Yet, little is known about the extent of fallow fields since fallow is not explicitly differentiated within the cropland class in any existing remote sensing-based land use/cover maps, regardless of the spatial scale. With a 10 m spatial resolution and a 5-day revisit frequency, Sentinel-2 satellite imagery made it possible to disentangle agricultural land into cropped and fallow fields, facilitated by Google Earth Engine (GEE) for big data handling. Here we produce the first Sahelian fallow field map at a 10 m resolution for the baseline year 2017, accomplished by designing a remote sensing driven protocol for generating reference data for mapping over large areas. Based on the 2015 Copernicus Dynamic Land Cover map at 100 m resolution, the extent of fallow fields in the cropland class is estimated to be 63% (403,617 km(2)) for the Sahel in 2017. Similar results are obtained for five contemporary cropland products, with fallow fields occupying 57-62% of the cropland area. Yet, it is noted that the total estimated area coverage depends on the quality of the different cropland products. The share of cropped fields within the Copernicus cropland area is found to be higher in the arid regions (200-300 mm rainfall) as compared to the semi-arid regions (300-600 mm rainfall). The woody cover fraction within cropped and fallow fields is found to have a reversed pattern between arid (higher woody cover in cropped fields) and semi-arid (higher woody cover in fallow fields) regions. The method developed, using cloud-based Earth Observation (EO) data and computation on the GEE platform, is expected to be reproducible for mapping the extent of fallow fields across global croplands. Future applications based on multi-year time series is expected to improve our understanding of crop-fallow rotation dynamics in grass fallow systems being key in teasing apart how cropland intensification and expansion affect environmental variables, such as soil fertility, crop yields and local livelihoods in low-income regions such as the Sahel.

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