A new dataset of global irrigation areas from 2001 to 2015

Nagaraj, Deepak; Proust, Eleanor; Todeschini, Alberto; Rulli, Maria Cristina; D’Odorico, Paolo

doi:10.1016/j.advwatres.2021.103910

Cited by 42 publications

(38 citation statements)

References 42 publications

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“…Data from optical sensors including Landsat, MODIS (Moderate Resolution Imaging Spectroradiometer), AVHRR (Advanced Very High-Resolution Radiometer), MERIS (Medium, Resolution Imaging spectrometer), and SPOT (Satellite pour l'Observation de la Terre) [4,[29][30][31][32], and their combination with other model-based and ground-based ancillary data [33], have been extensively used to map irrigated areas, making use of the difference in the spectral responses of irrigated and non-irrigated croplands. One of the first explicit attempts to use visible-and near-infrared remote sensing information for the detection of irrigated areas at the global scale is the International Water Management Institute Global Irrigated Area Map [23].…”

Section: Mapping Methodsmentioning

confidence: 99%

A Review of Irrigation Information Retrievals from Space and Their Utility for Users

et al. 2021

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Irrigation represents one of the most impactful human interventions in the terrestrial water cycle. Knowing the distribution and extent of irrigated areas as well as the amount of water used for irrigation plays a central role in modeling irrigation water requirements and quantifying the impact of irrigation on regional climate, river discharge, and groundwater depletion. Obtaining high-quality global information about irrigation is challenging, especially in terms of quantification of the water actually used for irrigation. Here, we review existing Earth observation datasets, models, and algorithms used for irrigation mapping and quantification from the field to the global scale. The current observation capacities are confronted with the results of a survey on user requirements on satellite-observed irrigation for agricultural water resources’ management. Based on this information, we identify current shortcomings of irrigation monitoring capabilities from space and phrase guidelines for potential future satellite missions and observation strategies.

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Section: Mapping Methodsmentioning

confidence: 99%

A Review of Irrigation Information Retrievals from Space and Their Utility for Users

et al. 2021

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“…Moreover, the amount of water loss due to seepage often falls within the discharge measurement errors with traditional methods. With new technologies, seepage losses can be determined more accurately and reliably [1,3].…”

Section: Discussionmentioning

confidence: 99%

“…Irrigation is crucially important in sustaining global food production, as nearly 40% of crop production takes place on irrigated land worldwide. Additionally, about 70% of global freshwater use is consumed by irrigation, using a great majority of freshwater than for industry and other human activities [1][2][3]. With the growing water needs of human societies, the constraining effect of the availability of water resources on global food security is very obvious.…”

Section: Introductionmentioning

confidence: 99%

A Collaborative Sensing System for Farmland Water Conservancy Project Maintenance through Integrating Satellite, Aerial, and Ground Observations

Chao

Fang

et al. 2021

Water

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More and more attention has been paid to farmland water conservancy project (FWCP) maintenance in China, which can reallocate water resources in a more rational and efficient manner. Compared with the traditional survey such as field survey, FWCP maintenance can be improved efficiently with geospatial technology. To improve the level of FWCP maintenance in China, a collaborative sensing system framework by integrating satellite, aerial, and ground remote sensing is put forward. The structure of the system framework includes three sections, namely the data acquisition, the operational work, and the application and service. Through the construction and operation of such collaborative sensing system, it will break through the limitation of any single remote sensing platform and provide all-around and real-time information on FWCP. The collaborative monitoring schemes for the designed FWCP maintenance can engage ditch riders to maintain more effectively, which will enable them to communicate more specifically with smallholders in the process of irrigation. Only when ditch riders and farmers are fully involved, irrigation efficiency will be improved. Furthermore, the collaborative sensing system needs feasible standards for multi-source remote sensing data processing and intelligent information extraction such as data fusion, data assimilation, and data mining. In a way, this will promote the application of remote sensing in the field of agricultural irrigation and water saving. On the whole, it will be helpful to improve the traditional maintenance problems and is also the guarantee for establishing a long-term scientific management mechanism of FWCP maintenance in developing countries, especially in China.

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“…Unlike global studies that have mapped irrigated areas at coarse scales (e.g. Thenkabail et al 2009, Siebert et al 2015, Nagaraj et al 2021 here we use Landsat imagery (30 m) to map irrigated areas during crop growing periods at the local scale. We propose methods based on the application of machine learning algorithms as an alternative to hydrologic calculations proposed by Rufin et al (2018) for those regions where detailed hydrologic data are not available.…”

Section: Introductionmentioning

confidence: 99%

Are African irrigation dam projects for large-scale agribusiness or small-scale farmers?

Tatlhego

D’Odorico

2022

Environ. Res. Commun.

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The economic development of rural economies across the global south is often related to access to water and the development of water infrastructure. It has been argued that the construction of new dams would unleash the agricultural potential of African nations that are exposed to seasonal water scarcity, strong interannual rainfall variability, and associated uncertainties in water availability. While water security is often presented as the pathway to poverty alleviation and invoked to justify large dam projects for irrigation, it is still unclear to what extent small holders will benefit from them. Are large dams built to the benefit of subsistence farmers or of large-scale commercial agriculture? Here we use remote sensing imagery in conjunction with advanced machine learning algorithms to map the irrigated areas (or ‘command areas’) that have appeared in the surroundings of 18 major dams built across the African continent between 2000 and 2015. We quantify the expansion of irrigation afforded by those dams, the associated changes in population density, forest cover, and farm size. We find that, while in the case of nine dams in the year 2000 there were no detectable farming patterns, in 2015 a substantial fraction of the command area (ranging between 8.5% and 96.7%) was taken by large-scale farms (i.e., parcels >200 ha). Seven of the remaining 9 dams showed a significant increase in average farm size and number of farms between 2000 and 2015, with large-scale farming accounting for anywhere between 5.2% and 76.7% of the command area. Collectively, these results indicate that many recent dam projects in Africa are associated either with the establishment of large-scale farming or a transition from small-scale to mid-to-large scale agriculture.

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A new dataset of global irrigation areas from 2001 to 2015

Cited by 42 publications

References 42 publications

A Review of Irrigation Information Retrievals from Space and Their Utility for Users

A Review of Irrigation Information Retrievals from Space and Their Utility for Users

A Collaborative Sensing System for Farmland Water Conservancy Project Maintenance through Integrating Satellite, Aerial, and Ground Observations

Are African irrigation dam projects for large-scale agribusiness or small-scale farmers?

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