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Research about Africa

Source-linked reports with geographic coverage including Africa.

At least 19 recordsLinked to original sources

VegET evapotranspiration for Africa: Continental-scale simulation, multi-product evaluation, and drought assessment

Study region Continental Africa, encompassing diverse climatic zones—tropical, arid, and temperate—and spanning major transboundary river basins such as the Nile, Niger, Congo, Volta, and Zambezi River Basins. The region exhibits pronounced hydroclimatic gradients and heterogeneous land use systems ranging from rainfed croplands and rangelands to dense tropical forests and irrigated schemes. Study focus Actual evapotranspiration (ETa) is a central component of the terrestrial water balance, governing the redistribution of water and energy between the land surface and the atmosphere. Accurate estimation of ETa at continental scale is critical for hydrological monitoring, water resource management, and climate adaptation, as well as for quantifying water, energy, and carbon fluxes that underpin sustainable development. In this study, we applied the agro-hydrologic VegET v2 model to simulate a new, high-resolution, continental-scale ETa dataset for Africa (2000–2021). The model results were benchmarked against four widely used remote sensing-based products—MODIS16 v6.1, SSEBop v6.1, WaPOR v3, and GLEAM v4.1a—across major climate zones, land use types, and River Basins, providing a comprehensive multi-product evaluation of evapotranspiration dynamics across the continent. New hydrological insights for the region Validation against eddy covariance flux tower observations at eight representative sites confirmed that VegET v2 accurately reproduces the seasonal dynamics of observed ETa, achieving a correlation (r) of 0.8 and an RMSE of 25 mm month⁻¹ —accuracy that is comparable to or higher than accuracies of satellite-based products MODIS16, SSEBop, and GLEAM. This study represents one of the first Africa-wide hydrological simulations of ETa, extending the VegET model beyond basin-scale applications. Intercomparisons reveal that VegET aligns closely with MODIS16, SSEBop, and GLEAM in humid and tropical regions (r = 0.80–0.90; RMSE < 20 mm month⁻¹), while greater discrepancies appear in arid and semi-arid zones, where WaPOR tends to overestimate ETa (RMSE ≥ 28 mm month⁻¹). Despite these differences, VegET effectively captures spatial and temporal ETa variability across rainfed croplands, forests, and savannas, supporting its utility in regional water balance assessments, water accounting, and drought monitoring. A key application of VegET v2 is the Evapotranspiration Deficit Index (ETDI), derived by integrating VegET-based ETa with potential evapotranspiration (PET) to quantify water stress. ETDI successfully captured major drought episodes across Africa, including persistent Sahelian and southern African dry spells, the 2020–2021 winter drought in the Maghreb, and the 2018–2019 austral summer drought in southern Africa, while identifying positive anomalies over central Africa indicative of recurrent wetness. These results underscore VegET’s capability as a hydrologically consistent, operational tool for continental ETa monitoring and drought assessment, offering support for basin-scale water balance studies, food security planning, and climate resilience across Africa’s diverse hydrological environments.

Journal of Hydrology: Regional Studies↗

Advancing water security in Africa with new high-resolution discharge data

VegDischarge v1 is a comprehensive river discharge across Africa (2000–2021), produced by coupling the agro-hydrologic VegET model and the mizuRoute routing framework. Using remote sensing data and hydrological modeling, the 1-km runoff field simulated by VegET, and routed with mizuRoute, covers over 64,000 river segments in Africa. The VegET model simulates runoff based on vegetation and soil moisture dynamics, while mizuRoute processes this runoff through a detailed river network. Performance metrics show strong model reliability, with R² ranging from 0.5 to 0.9, NSE between 0.6 and 0.9, and KGE from 0.5 to 0.8. The total annual average discharge for Africa is quantified at 3238.1 km³ . year-1, with contributions to various oceanic basins: 989.9 km³ . year-1 to the North Atlantic, primarily from West African rivers like the Senegal, Gambia, Volta, and Niger; 1313.7 km³ . year-1 to the South Atlantic, largely from the Congo River; 212.5 km³ . year-1 to the Mediterranean Sea, predominantly from the Nile River; and 722.0 km³ . year-1 to the Indian Ocean, with substantial inputs from rivers such as the Zambezi. This VegDischarge v1 is valuable for policymakers, stakeholders, and researchers to better understand water availability, its temporal and spatial variations, that impact water-related infrastructure planning, sustainable resource allocation, and the development of climate resilience mitigation strategies.

Scientific Data↗

Developments in African industrial minerals for renewable energy

Introduction Africa is emerging as a leading source for minerals used in the manufacture of batteries for electric vehicles and in other renewable energy applications. New graphite, lithium, and rare-earth mines have or could be opened in African countries from 2017 through 2026. Estimates of production capacities for graphite, lithium, and rare-earth mines for 2023 and beyond are based upon supply-side assumptions, such as announced plans for new capacity construction and bankable feasibility studies, as well as projected trends that could affect current producing facilities in 2023 and planned new facilities projected to come online by 2026. Forward-looking information, including estimates of future production capacities, graphite flake distributions, and timing of the start of operations, are subject to risk factors and uncertainties that could cause actual events or results to differ significantly from expected outcomes. Projects listed in this report are presented as an indication of industry plans and are not a U.S. Geological Survey (USGS) prediction of what will take place. Only projects with planned startup dates are included in this report; ther graphite, lithium, and rare-earth projects in Africa without startup dates were known to be in various stages of development but are not included in this fact sheet.

Fact Sheet↗

Geospatial PDF map of the compilation of GIS data for the mineral industries and related infrastructure of Africa

Introduction In 2021, the U.S. Geological Survey's (USGS) National Minerals Information Center (NMIC) completed the project titled "Compilation of geospatial data for the mineral industries and related infrastructure of Africa." This project aimed to leverage the expertise and capabilities of the NMIC to collect, synthesize, and interpret geospatial data to inform on the extractive resources of the African region and expand the NMIC's understanding on the impact of mineral industry of African nations in the global economy. The African region, which comprises the independent nations that make up the African continent and its associated islands and dependencies, consists of a total of 58 mineral producing countries. The primary objective of this effort was to create a fully attributed Geographic Information System (GIS) portraying existing mining infrastructure, resources, and development capacity across Africa along with the related infrastructure capable of supporting current (for the reference year 2018) and future extractive industry operations in the region. The compiled GIS geodatabase with supporting documentation including comprehensive metadata was published as a USGS data release titled "Compilation of Geospatial Data (GIS) for the Mineral Industries and Related Infrastructure of Africa." This georeferenced portable document format (GeoPDF) map sheet presents a new geographic information product containing a partial representation of the GIS data. This GeoPDF map provides a visual comparison of the distribution of mineral industry and related infrastructure GIS data, which contributes to a deeper understanding of the intersections and complexities of the extractive industries within Africa.

Open-File Report↗

A framework for disaggregating remote-sensing cropland into rainfed and irrigated classes at continental scale

Agriculture consumes the largest share of freshwater globally; therefore, distinguishing between rainfed and irrigated croplands is essential for agricultural water management and food security. In this study, a framework incorporating the Budyko model was used to differentiate between rainfed and irrigated cropland areas in Africa for eight remote sensing landcover products and a high-confidence cropland map (HCCM). The HCCM was generated for calibration and validation of the crop partitioning framework as an alternative to individual cropland masks which exhibit high disagreement. The accuracy of the framework in partitioning the HCCM was evaluated using an independent validation dataset, yielding an overall accuracy rate of 73 %. The findings of this study indicate that out of the total area covered by the HCCM (2.36 million km 2 ), about 461,000 km 2 (19 %) is irrigated cropland. The partitioning framework was applied on eight landcover products, and the extent of irrigated areas varied between 19 % and 30 % of the total cropland area. The framework demonstrated high precision and specificity scores, indicating its effectiveness in correctly identifying irrigated areas while minimizing the misclassification of rainfed areas as irrigated. This study provides an enhanced understanding of rainfed and irrigation patterns across Africa, supporting efforts towards achieving sustainable and resilient agricultural systems. Consequently, the approach outlined expands on the suite of remote sensing landcover products that can be used for agricultural water studies in Africa by enabling the extraction of irrigated and rainfed cropland data from landcover products that do not have disaggregated cropland classes.

International Journal of Applied Earth Observation↗

Drivers and facilitators of the illegal killing of elephants across 64 African sites

Ivory poaching continues to threaten African elephants. We (1) used criminology theory and literature evidence to generate hypotheses about factors that may drive, facilitate or motivate poaching, (2) identified datasets representing these factors, and (3) tested those factors with strong hypotheses and sufficient data quality for empirical associations with poaching. We advance on previous analyses of correlates of elephant poaching by using additional poaching data and leveraging new datasets for previously untested explanatory variables. Using data on 10 286 illegally killed elephants detected at 64 sites in 30 African countries (2002–2020), we found strong evidence to support the hypotheses that the illegal killing of elephants is associated with poor national governance, low law enforcement capacity, low household wealth and health, and global elephant ivory prices. Forest elephant populations suffered higher rates of illegal killing than savannah elephants. We found only weak evidence that armed conflicts may increase the illegal killing of elephants, and no evidence for effects of site accessibility, vegetation density, elephant population density, precipitation or site area. Results suggest that addressing wider systemic challenges of human development, corruption and consumer demand would help reduce poaching, corroborating broader work highlighting these more ultimate drivers of the global illegal wildlife trade.

Proceedings of the Royal Society B: Biological Sci↗

Animal tracing with sulfur isotopes: Spatial segregation and climate variability in Africa likely contribute to population trends of a migratory songbird

Climatic conditions affect animals but range-wide impacts at the population level remain largely unknown, especially in migratory species. However, studying climate–population relationships is still challenging in small migrants due to a lack of efficient and cost-effective geographic tracking method. Spatial distribution patterns of environmental stable isotopes (so called ‘isoscapes’) generally overcome these limitations but none of the currently available isoscapes provide a substantial longitudinal gradient in species-rich sub-Saharan Africa. In this region, sulphur ( δ 34 S) has not been sufficiently explored on a larger scale. We developed a δ 34 S isoscape to trace animal origins in sub-Saharan Africa by coupling known-origin samples from tracked migratory birds with continental remotely sensed environmental data building on environment– δ 34 S relationships using a flexible machine learning technique. Furthermore, we link population-specific nonbreeding grounds with interannual climatic variation that might translate to breeding population trends. The predicted δ 34 S isotopic map featured east–west and coast-to-inland isotopic gradients and was applied to predict nonbreeding grounds of three breeding populations of Eurasian Reed Warblers Acrocephalus scirpaceus with two distinct migratory phenotypes. Breeding populations as well as migratory phenotypes exhibited large-scale segregation within the African nonbreeding range. These regions also differed substantially in the interannual climatic variation, with higher interannual variability in the eastern part of the range during 2001–2012. Over the same period, the eastern European breeding population seemed to have experienced a more steep decline in population size. The link between migratory patterns and large-scale climatic variability appears important to better understand population trajectories in many declining migratory animals. We believe animal tracing using sulphur isotopes will facilitate these efforts and offers manifold ecological and forensic applications in the biodiversity hotspot of sub-Saharan Africa.

Journal of Animal Ecology↗

Remotely sensed thermal decay rate: An index for vegetation monitoring

Vegetation buffers local diurnal land surface temperatures, however, this effect has found limited applications for remote vegetation characterization. In this work, we parameterize diurnal temperature variations as the thermal decay rate derived by using satellite daytime and nighttime land surface temperatures and modeled using Newton’s law of cooling. The relationship between the thermal decay rate and vegetation depends on many factors including vegetation type, size, water content, location, and local conditions. The theoretical relationships are elucidated, and empirical relationships are presented. Results show that the decay rate summarizes both vegetation structure and function and exhibits a high correlation with other established vegetation-related observations. As proof of concept, we interpret 15-year spatially explicit trends in the annual thermal decay rates over Africa and discuss results. Given recent increases in availability of finer spatial resolution satellite thermal measurements, the thermal decay rate may be a useful index for monitoring vegetation.

Nature↗

A pan-African high-resolution drought index dataset

Droughts in Africa cause severe problems, such as crop failure, food shortages, famine, epidemics and even mass migration. To minimize the effects of drought on water and food security on Africa, a high-resolution drought dataset is essential to establish robust drought hazard probabilities and to assess drought vulnerability considering a multi- and cross-sectional perspective that includes crops, hydrological systems, rangeland and environmental systems. Such assessments are essential for policymakers, their advisors and other stakeholders to respond to the pressing humanitarian issues caused by these environmental hazards. In this study, a high spatial resolution Standardized Precipitation-Evapotranspiration Index (SPEI) drought dataset is presented to support these assessments. We compute historical SPEI data based on Climate Hazards group InfraRed Precipitation with Station data (CHIRPS) precipitation estimates and Global Land Evaporation Amsterdam Model (GLEAM) potential evaporation estimates. The high-resolution SPEI dataset (SPEI-HR) presented here spans from 1981 to 2016 (36 years) with 5 km spatial resolution over the whole of Africa. To facilitate the diagnosis of droughts of different durations, accumulation periods from 1 to 48 months are provided. The quality of the resulting dataset was compared with coarse-resolution SPEI based on Climatic Research Unit (CRU) Time Series (TS) datasets, Normalized Difference Vegetation Index (NDVI) calculated from the Global Inventory Monitoring and Modeling System (GIMMS) project and root zone soil moisture modelled by GLEAM. Agreement found between coarse-resolution SPEI from CRU TS (SPEI-CRU) and the developed SPEI-HR provides confidence in the estimation of temporal and spatial variability of droughts in Africa with SPEI-HR. In addition, agreement of SPEI-HR versus NDVI and root zone soil moisture – with an average correlation coefficient ( R ) of 0.54 and 0.77, respectively – further implies that SPEI-HR can provide valuable information for the study of drought-related processes and societal impacts at sub-basin and district scales in Africa. The dataset is archived in Centre for Environmental Data Analysis (CEDA) via the following link: https://doi.org/10.5285/bbdfd09a04304158b366777eba0d2aeb (Peng et al., 2019a).

Earth System Science Data↗

Genetic identification of African pangolins and their origin in illegal trade

To track the illegal pangolin trade from Africa to Asia, we analyzed 1800 DNA samples from 30 seizures of African pangolin scales in Hong Kong during the period 2012–2016. We concluded that all four African pangolin species were present in trade, and that the white-bellied pangolin ( Phataginus tricuspis ) appeared most frequently (88.5%) in our samples. All six previously described phylogeographic lineages originating from the entire distribution range of P. tricuspis were found in the seizures, and the western central African lineage alone accounted for 67.1% of the samples of this species. Confirmed by modelling data, high DNA haplotype richness was present in most of the pangolin scale seizures, including those contained in small air parcels and large-volume sea shipments. Results suggest that African pangolins were hunted across large areas of their natural range and then delivered to a small number of trade transit hubs. Our study illustrates the utility of genetic analysis for characterizing the illegal pangolin trade and identifying the geographic origin of poaching hotspots.

Global Ecology and Conservation↗

Upper mantle earth structure in Africa from full-wave ambient noise tomography

Our understanding of the tectonic development of the African continent and the interplay between its geological provinces is hindered by unevenly distributed seismic instrumentation. In order to better understand the continent, we used long-period ambient noise full waveform tomography on data collected from 186 broadband seismic stations throughout Africa and surrounding regions to better image the upper mantle structure. We extracted empirical Green’s functions from ambient seismic noise using a frequency-time normalization method and retrieved coherent signal at periods of 7-340 seconds. We simulated wave propagation through a heterogeneous Earth using a spherical finite-difference approach to obtain synthetic waveforms, measured the misfit as phase delay between the data and synthetics, calculated numerical sensitivity kernels using the scattering integral approach, and iteratively inverted for structure. The resulting images of isotropic, shear wavespeed for the continent reveal segmented, low-velocity upper mantle beneath the highly magmatic northern and eastern sections of the East African Rift System (EARS). In the southern and western sections, high-velocity upper mantle dominates, and distinct, low-velocity anomalies are restricted to regions of current volcanism. At deeper depths, the southern and western EARS transitions to low-velocities. In addition to the EARS, several low-velocity anomalies are scattered through the shallow upper mantle beneath Angola and North Africa, and some of these low-velocity anomalies may be connected to a deeper feature. Distinct upper mantle high-velocity anomalies are imaged throughout the continent and suggest multiple cratonic roots within the Congo region, and possible cratonic roots within the Sahara Metacraton.

Geochemistry, Geophysics, Geosystems↗

Validation of the CHIRPS satellite rainfall estimates over eastern Africa

Long and temporally consistent rainfall time series are essential in climate analyses and applications. Rainfall data from station observations are inadequate over many parts of the world due to sparse or non-existent observation networks, or limited reporting of gauge observations. As a result, satellite rainfall estimates have been used as an alternative or as a supplement to station observations. However, many satellite-based rainfall products with long time series suffer from coarse spatial and temporal resolutions and inhomogeneities caused by variations in satellite inputs. There are some satellite rainfall products with reasonably consistent time series, but they are often limited to specific geographic areas. The Climate Hazards Group Infrared Precipitation (CHIRP) and CHIRP combined with station observations (CHIRPS) are recently produced satellite-based rainfall products with relatively high spatial and temporal resolutions and quasi-global coverage. In this study, CHIRP and CHIRPS were evaluated over East Africa at daily, dekadal (10-day) and monthly time-scales. The evaluation was done by comparing the satellite products with rain-gauge data from about 1,200 stations. The CHIRP and CHIRPS products were also compared with two similar operational satellite rainfall products: the African Rainfall Climatology version 2 (ARC2) and the Tropical Applications of Meteorology using Satellite data (TAMSAT). The results show that both CHIRP and CHIRPS products are significantly better than ARC2 with higher skill and low or no bias. These products were also found to be slightly better than the latest version of the TAMSAT product at dekadal and monthly time-scales, while TAMSAT performed better at the daily time-scale. The performance of the different satellite products exhibits high spatial variability with weak performances over coastal and mountainous regions.

Africa↗

Examining the role of unusually warm Indo‐Pacific sea‐surface temperatures in recent African droughts

Southern Africa (SA) and eastern Africa (EA) experienced a sequence of severe droughts in December–February (SA DJF) 2015–2016, October–December (EA OND) 2016 and March–April–May 2017 (EA MAM). This sequence contributed to severe food insecurity. While climate variability in these regions is very complex, the goal of this study is to analyse the role played by unusually warm Indo–Pacific SSTs, where unusual is defined as a 1‐in‐6 year event. We use observed sea‐surface temperatures (SST) and satellite–gauge rainfall observations, a 20‐member ensemble of Community Atmospheric Model version 5.1 simulations (CAM5), and a 40‐member ensemble of climate change simulations from the Community Earth Systems Model version 1 (CESM1) Large Ensemble Community Project (LENS) to explore climate conditions associated with warm events identified based on eastern and western Pacific SSTs. Our analysis suggests that strong El Niño's may be followed by warm western Pacific SST conditions, which can lead to conditions conducive to successive and potentially predictable droughts in SA DJF, EA OND and EA MAM. We show that different regions of warm SST are related to recent droughts—SA DJF: Niño 3.4; EA OND: western equatorial Pacific (WEP); and EA MAM: western North Pacific (WNP). For DJF and MAM, respectively, the CAM5 model driven with observed SST and the same model driven within a climate change experiment indicate that warmer El Niño's and WNP events produce more intense atmospheric responses, potentially associated with more severe droughts. OND climate seems to be strongly influenced by the Indian Ocean Dipole, which corresponds with some WEP events. Given global warming, we suggest that the extreme Niño 3.4 and west Pacific SST events responsible for 2015–2017 droughts are likely to reoccur, thus humanitarian agencies should prepare to predict and respond to multi‐year drought and substantial food insecurity in SA and EA.

Journal of the Royal Meteorological Society↗

Rainfall over the African continent from the 19th through the 21st century

Most of the African continent is semi-arid and hence prone to extreme variations in rainfall from year to year. The extreme droughts that have plagued the Sahel and eastern Africa are particularly well known. This article uses a markedly expanded and updated rainfall data set to examine rainfall variability in 13 sectors that cover most of the continent. Annual rainfall is presented for each sector; the March-to-May and October–November seasons are also examined for equatorial sectors. In each case, the article includes the longest and most comprehensive precipitation gauge series ever published. All time series cover at least a century and most cover roughly one and one-half centuries or more. Although towards the end of the 20th century there was a widespread trend towards more arid conditions, few significant trends are evident over the entire period of record. The largest were downward trends in the Sahel and western sectors of North Africa. In those regions, an abrupt reduction in rainfall occurred around 1968, but a synchronous change occurred many other parts of Africa. A recovery did occur in the Sahel, but to varying degrees across the east-west expanse of the region. Noteworthy is that the west-to-east rainfall gradient across the region appears to have weakened in recent decades. For the continent as a whole, another change began in the 1980s decade, with more arid conditions persisting at the continental scale until early in the twenty-first century. No other such period of dry conditions occurred within the roughly one and one-half centuries evaluated here. A notable change also occurred at the seasonal level. During the period 1980 to 1998 rainfall during March-to-May was well below the long-term mean throughout most of the area from 20° N to 35° S. At the same time rainfall was above the long-term mean in most of eastern sectors within this latitude span, indicating a change in the seasonality of rainfall of a large part of Africa.

Global and Planetary Change↗

Nominal 30-m cropland extent map of continental Africa by integrating pixel-based and object-based algorithms using Sentinel-2 and Landsat-8 Data on Google Earth Engine

A satellite-derived cropland extent map at high spatial resolution (30-m or better) is a must for food and water security analysis. Precise and accurate global cropland extent maps, indicating cropland and non-cropland areas, are starting points to develop higher-level products such as crop watering methods (irrigated or rainfed), cropping intensities (e.g., single, double, or continuous cropping), crop types, cropland fallows, as well as for assessment of cropland productivity (productivity per unit of land), and crop water productivity (productivity per unit of water). Uncertainties associated with the cropland extent map have cascading effects on all higher-level cropland products. However, precise and accurate cropland extent maps at high spatial resolution over large areas (e.g., continents or the globe) are challenging to produce due to the small-holder dominant agricultural systems like those found in most of Africa and Asia. Cloud-based geospatial computing platforms and multi-date, multi-sensor satellite image inventories on Google Earth Engine offer opportunities for mapping croplands with precision and accuracy over large areas that satisfy the requirements of broad range of applications. Such maps are expected to provide highly significant improvements compared to existing products, which tend to be coarser in resolution, and often fail to capture fragmented small-holder farms especially in regions with high dynamic change within and across years. To overcome these limitations, in this research we present an approach for cropland extent mapping at high spatial resolution (30-m or better) using the 10-day, 10 to 20-m, Sentinel-2 data in combination with 16-day, 30-m, Landsat-8 data on Google Earth Engine (GEE). First, nominal 30-m resolution satellite imagery composites were created from 36,924 scenes of Sentinel-2 and Landsat-8 images for the entire African continent in 2015–2016.

Remote Sensing↗

Automated cropland mapping of continental Africa using Google Earth Engine cloud computing

The automation of agricultural mapping using satellite-derived remotely sensed data remains a challenge in Africa because of the heterogeneous and fragmental landscape, complex crop cycles, and limited access to local knowledge. Currently, consistent, continent-wide routine cropland mapping of Africa does not exist, with most studies focused either on certain portions of the continent or at most a one-time effort at mapping the continent at coarse resolution remote sensing. In this research, we addressed these limitations by applying an automated cropland mapping algorithm (ACMA) that captures extensive knowledge on the croplands of Africa available through: (a) ground-based training samples, (b) very high (sub-meter to five-meter) resolution imagery (VHRI), and (c) local knowledge captured during field visits and/or sourced from country reports and literature. The study used 16-day time-series of Moderate Resolution Imaging Spectroradiometer (MODIS) normalized difference vegetation index (NDVI) composited data at 250-m resolution for the entire African continent. Based on these data, the study first produced accurate reference cropland layers or RCLs (cropland extent/areas, irrigation versus rainfed, cropping intensities, crop dominance, and croplands versus cropland fallows) for the year 2014 that provided an overall accuracy of around 90% for crop extent in different agro-ecological zones (AEZs). The RCLs for the year 2014 (RCL2014) were then used in the development of the ACMA algorithm to create ACMA-derived cropland layers for 2014 (ACL2014). ACL2014 when compared pixel-by-pixel with the RCL2014 had an overall similarity greater than 95%. Based on the ACL2014, the African continent had 296 Mha of net cropland areas (260 Mha cultivated plus 36 Mha fallows) and 330 Mha of gross cropland areas. Of the 260 Mha of net cropland areas cultivated during 2014, 90.6% (236 Mha) was rainfed and just 9.4% (24 Mha) was irrigated. Africa has about 15% of the world’s population, but only about 6% of world’s irrigation. Net cropland area distribution was 95 Mha during season 1, 117 Mha during season 2, and 84 Mha continuous. About 58% of the rainfed and 39% of the irrigated were single crops (net cropland area without cropland fallows) cropped during either season 1 (January-May) or season 2 (June-September). The ACMA algorithm was deployed on Google Earth Engine (GEE) cloud computing platform and applied on MODIS time-series data from 2003 through 2014 to obtain ACMA-derived cropland layers for these years (ACL2003 to ACL2014). The results indicated that over these twelve years, on average: (a) croplands increased by 1 Mha/yr, and (b) cropland fallows decreased by 1 Mha/year. Cropland areas computed from ACL2014 for the 55 African countries were largely underestimated when compared with an independent source of census-based cropland data, with a root-mean-square error (RMSE) of 3.5 Mha. ACMA demonstrated the ability to hind-cast (past years), now-cast (present year), and forecast (future years) cropland products using MODIS 250-m time-series data rapidly, but currently, insufficient reference data exist to rigorously report trends from these results.

ISPRS Journal of Photogrammetry and Remote Sensing↗

The Centennial Trends Greater Horn of Africa precipitation dataset

East Africa is a drought prone, food and water insecure region with a highly variable climate. This complexity makes rainfall estimation challenging, and this challenge is compounded by low rain gauge densities and inhomogeneous monitoring networks. The dearth of observations is particularly problematic over the past decade, since the number of records in globally accessible archives has fallen precipitously. This lack of data coincides with an increasing scientific and humanitarian need to place recent seasonal and multi-annual East African precipitation extremes in a deep historic context. To serve this need, scientists from the UC Santa Barbara Climate Hazards Group and Florida State University have pooled their station archives and expertise to produce a high quality gridded ‘Centennial Trends’ precipitation dataset. Additional observations have been acquired from the national meteorological agencies and augmented with data provided by other universities. Extensive quality control of the data was carried out and seasonal anomalies interpolated using kriging. This paper documents the CenTrends methodology and data.

Scientific Data↗