Linking multidimensional cropland ecosystem health assessment, spatialized dominant-driver diagnosis and mechanism-informed zoning in the middle and lower Yellow River, China - Shanshan Guo; Peter M. Atkinson; Junchang Huang; Hejie Wei; Tingyuan Zhou; Ling Li (Agricultural Systems, 2026)

UTCMapper for 0.3 m urban tree canopy mapping: A case study in Shanghai - Shuang Zhang; Qunming Wang; Qiquan Yang; Xiaohua Tong; Peter M. Atkinson (Remote Sensing of Environment, 2026)

Unveiling small-scale tropical forest loss and post-loss recovery in the Congo Basin - Yihang Zhang; Xiaodong Li; Feng Ling; Xia Wang; Yun Du; Peter M. Atkinson (Global Environmental Change, 2026)

The dynamic response of vegetation water use efficiency to wildfire disturbances in the Northern Hemisphere - Huipeng Xi; Qunming Wang; Peter M. Atkinson (Agricultural and Forest Meteorology, 2026)

Crowd detection using Very-Fine-Resolution satellite imagery - Tong Xiao; Qunming Wang; Ping Lu; Tenghai Huang; Xiaohua Tong; Peter M. Atkinson (ISPRS Journal of Photogrammetry and Remote Sensing, 2026)

Diarrhoea in children under 5 years in two informal settlements in Accra, Ghana: The impact of antecedent rainfall and flooding - Mehmet A. Veral; Manoj Roy; Roger W. Pickup; Richard Bayitse; Pat M. Agbedor; Mark Akrong; Peter M. Atkinson (Environmental Research, 2026)

Establishing a Historical Fine-Resolution Urban Database from KH-9 HEXAGON MCS and PCS Imagery Including an Urban Landscape Map, Stereo Anaglyph Image and Digital Surface Model - AmirReza Shahtahmassebi; Golnaz Shahtahmassebi; Nathan Moore; Peter M. Atkinson (PFG – Journal of Photogrammetry, Remote Sensing and Geoinformation Science, 2025)

Mapping tropical dry Miombo woodlands into functional forest classes using Sentinel-1 and Sentinel-2 imagery and machine learning - Kennedy Kanja; Ce Zhang; Melvin Lippe; Peter M. Atkinson (Remote Sensing Applications: Society and Environment, 2025)

GLOSTFM: A global spatiotemporal fusion model integrating multi-source satellite observations to enhance land surface temperature resolution - Qingyan Meng; Shize Chen; Linlin Zhang; Xiaolin Zhu; Yeping Zhang; Peter M. Atkinson (Remote Sensing of Environment, 2025)

Unsupervised object-based spectral unmixing for subpixel mapping - Chengyuan Zhang; Qunming Wang; Peter M. Atkinson (Remote Sensing of Environment, 2025)

Data fidelity-oriented spatial-spectral fusion of CRISM and CTX images - Qunming Wang; Wenjing Ma; Sicong Liu; Xiaohua Tong; Peter M. Atkinson (ISPRS Journal of Photogrammetry and Remote Sensing, 2025)

An efficient and generalisable approach for mapping paddy rice fields based on their unique spectra during the transplanting period leveraging the CIE colour space - Huapeng Li; Jujian Huang; Ce Zhang; Xiangyu Ning; Shuqing Zhang; Peter M. Atkinson (Remote Sensing of Environment, 2024)

Combination and summary of ATLAS dark matter searches interpreted in a 2HDM with a pseudo-scalar mediator using 139 fb−1 of s = 13 TeV pp collision data - G. Aad; B. Abbott; K. Abeling; N.J. Abicht; S.H. Abidi; A. Aboulhorma; H. Abramowicz; H. Abreu; Y. Abulaiti; A.C. Abusleme Hoffman; B.S. Acharya; C. Adam Bourdarios; et al. (Science Bulletin, 2024)

Identifying fine-scale archaeological features using KH-9 HEXAGON mapping and panoramic camera images: evidence from Liangzhu Ancient City - Amir Reza Shahtahmassebi; Golnaz Shahtahmassebi; Nathan Moore; Peter M. Atkinson (International Journal of Remote Sensing, 2024)

Ensembles of multiple models for soil moisture retrieval from remote sensing data over agricultural areas: A deep learning-based framework - Amir Sedighi; Saeid Hamzeh; Seyed Kazem Alavipanah; Abd Ali Naseri; Peter M. Atkinson (Remote Sensing Applications: Society and Environment, 2024)

TSI-Siamnet: A Siamese network for cloud and shadow detection based on time-series cloudy images - Qunming Wang; Jiayi Li; Xiaohua Tong; Peter M. Atkinson (ISPRS Journal of Photogrammetry and Remote Sensing, 2024)

Filling gaps in cloudy Landsat LST product by spatial-temporal fusion of multi-scale data - Qunming Wang; Yijie Tang; Xiaohua Tong; Peter M. Atkinson (Remote Sensing of Environment, 2024)

A novel surface energy balance-based approach to land surface temperature downscaling - Mohammad Karimi Firozjaei; Naeim Mijani; Majid Kiavarz; Si-Bo Duan; Peter M. Atkinson; Seyed Kazem Alavipanah (Remote Sensing of Environment, 2024)

Automatic mapping of 500 m daily open water body fraction in the American continent using GOES-16 ABI imagery - Xia Wang; Peter M. Atkinson; Yihang Zhang; Xiaodong Li; Kerong Zhang (Remote Sensing of Environment, 2024)

Very fine spatial resolution urban land cover mapping using an explicable sub-pixel mapping network based on learnable spatial correlation - Da He; Qian Shi; Jingqian Xue; Peter M. Atkinson; Xiaoping Liu (Remote Sensing of Environment, 2023)

Spatio-temporal multi-level attention crop mapping method using time-series SAR imagery - Zhu Han; Ce Zhang; Lianru Gao; Zhiqiang Zeng; Bing Zhang; Peter M. Atkinson (ISPRS Journal of Photogrammetry and Remote Sensing, 2023)

Monitoring monthly tropical humid forest disturbances with Planet NICFI images in Cameroon - Yihang Zhang; Xia Wang; Xiaodong Li; Yun Du; Peter M. Atkinson (Agricultural and Forest Meteorology, 2023)

Unpaired spatio-temporal fusion of image patches (USTFIP) from cloud covered images - Harkaitz Goyena; Unai Pérez-Goya; Manuel Montesino-SanMartin; Ana F. Militino; Qunming Wang; Peter M. Atkinson; M. Dolores Ugarte (Remote Sensing of Environment, 2023)

A novel Greenness and Water Content Composite Index (GWCCI) for soybean mapping from single remotely sensed multispectral images - Hui Chen; Huapeng Li; Zhao Liu; Ce Zhang; Shuqing Zhang; Peter M. Atkinson (Remote Sensing of Environment, 2023)

Combining UAV and Sentinel-2 satellite multi-spectral images to diagnose crop growth and N status in winter wheat at the county scale - Jie Jiang; Peter M. Atkinson; Chunsheng Chen; Qiang Cao; Yongchao Tian; Yan Zhu; Xiaojun Liu; Weixing Cao (Field Crops Research, 2023)

Pathways to achieving nature-positive and carbon–neutral land use and food systems in Wales - Sarah M. Jones; Alison C. Smith; Nicholas Leach; Peter Henrys; Peter M. Atkinson; Paula A. Harrison (Regional Environmental Change, 2023)
Land use and its management can play a vital role in carbon sequestration, but trade-offs may exist with other objectives including food security and nature recovery. Using an integrated model (the FABLE calculator), four pathways, co-created with colleagues at the Welsh Government, towards achieving climate and biodiversity targets in Wales were explored: status quo, improvements on current trends, land sparing and land sharing. We found that continuing as usual will not be sufficient to meet Wales’s climate and biodiversity targets. In contrast, the land use and agricultural sector became a net carbon sink in both the land sparing and land sharing pathways, through high afforestation targets, peatland restoration, reducing food waste and moving towards a healthier diet. Whilst both pathways released land for biodiversity, the gains were greater in the land sharing pathway, which was also less dependent on optimistic assumptions concerning productivity improvements. The results demonstrate that alternative approaches to achieving nature-positive and carbon–neutral land use and food systems may be possible, but they come with stringent and transformative requirements for policy changes, with an integrated approach necessary to maximise benefits for climate, food and nature.

Modelling and forecasting the effects of increasing sea surface temperature on coral bleaching in the Indo-Pacific region - Idham Khalil; Aidy M. Muslim; Mohammad Shawkat Hossain; Peter M. Atkinson (International Journal of Remote Sensing, 2023)

Rare germline variants in the AXIN2 gene in families with colonic polyposis and colorectal cancer - James M. Chan; Mark Clendenning; Sharelle Joseland; Peter Georgeson; Khalid Mahmood; Romy Walker; Julia Como; Jihoon E. Joo; Susan Preston; Ryan A. Hutchinson; Bernard J. Pope; Andrew Metz; et al. (Familial Cancer, 2022)

A joint distribution framework to improve presence‐only species distribution models by exploiting opportunistic surveys - Juan M. Escamilla Molgora; Luigi Sedda; Peter Diggle; Peter M. Atkinson (Journal of Biogeography, 2022)
Aim The availability of data related to species occurrences has favoured the development of species distribution models using only observations of presence. These data are intrinsically biased by the sampling effort. Presence‐only (PO) species distribution models (SDM) typically account for this effect by introducing additional data considered to be related with the sampling. This approach, however, does not allow the characterisation of the sampling effort and hinders the interpretation of the model. Here, we propose a Bayesian framework for PO SDMs that can explicitly model the sampling effect. Location Mexico. Taxon Pines, flycatchers (family Tyranidae), birds and plants. Methods The framework defines a bivariate process separable into ecological and sampling effort processes. PO data are conceived of incomplete observations where some presences have been filtered out. A choosing principle is used to separate out presences, missing data and absences relative to the species of interest and the sampling observations. The framework provides three modelling alternatives to account for a spatial autocorrelation structure: independent latent variables (model I); common latent spatial random effect (model II) and correlated latent spatial random effects (model III). The framework was compared against the Maximum Entropy (MaxEnt) algorithm in two case studies: one for the prediction of pines and another for the prediction of flycatchers. Results In both case studies, at least one of the proposed models achieved higher predictive accuracy than MaxEnt. The model III fit best when the sampling effort was informative, while model II was more suitable in cases with a high proportion of non‐sampled sites. Main Conclusions Our approach provides a flexible framework for PO SDMs aided by a sampling effort process informed by the accumulated observations of independent and heterogeneous surveys. For the two case studies, the framework provided a model with a higher predictive accuracy than an optimised version of MaxEnt.

Chronic kidney disease of unknown origin is associated with environmental urbanisation in Belfast, UK - Jennifer M. McKinley; Ute Mueller; Peter M. Atkinson; Ulrich Ofterdinger; Siobhan F. Cox; Rory Doherty; Damian Fogarty; J. J. Egozcue; V. Pawlowsky-Glahn (Environmental Geochemistry and Health, 2021)
Chronic kidney disease (CKD), a collective term for many causes of progressive renal failure, is increasing worldwide due to ageing, obesity and diabetes. However, these factors cannot explain the many environmental clusters of renal disease that are known to occur globally. This study uses data from the UK Renal Registry (UKRR) including CKD of uncertain aetiology (CKDu) to investigate environmental factors in Belfast, UK. Urbanisation has been reported to have an increasing impact on soils. Using an urban soil geochemistry database of elemental concentrations of potentially toxic elements (PTEs), we investigated the association of the standardised incidence rates (SIRs) of both CKD and CKD of uncertain aetiology (CKDu) with environmental factors (PTEs), controlling for social deprivation. A compositional data analysis approach was used through balances (a special class of log contrasts) to identify elemental balances associated with CKDu. A statistically significant relationship was observed between CKD with the social deprivation measures of employment, income and education (significance levels of 0.001, 0.01 and 0.001, respectively), which have been used as a proxy for socio-economic factors such as smoking. Using three alternative regression methods (linear, generalised linear and Tweedie models), the elemental balances of Cr/Ni and As/Mo were found to produce the largest correlation with CKDu. Geogenic and atmospheric pollution deposition, traffic and brake wear emissions have been cited as sources for these PTEs which have been linked to kidney damage. This research, thus, sheds light on the increasing global burden of CKD and, in particular, the environmental and anthropogenic factors that may be linked to CKDu, particularly environmental PTEs linked to urbanisation.

Risk assessment of the step-by-step return-to-work policy in Beijing following the COVID-19 epidemic peak - Wen-bin Zhang; Yong Ge; Mengxiao Liu; Peter M. Atkinson; Jinfeng Wang; Xining Zhang; Zhaoxing Tian (Stochastic Environmental Research and Risk Assessment, 2021)

A Special Issue on the Importance of Geostatistics in the Era of Data Science - Jennifer M. McKinley; Peter M. Atkinson (Mathematical Geosciences, 2020)

A Geostatistical Filter for Remote Sensing Image Enhancement - Qunming Wang; Xiaohua Tong; Peter M. Atkinson (Mathematical Geosciences, 2020)

Collective influence of household and community capitals on agricultural employment as a measure of rural poverty in the Mahanadi Delta, India - Tristan Berchoux; Gary R. Watmough; Fiifi Amoako Johnson; Craig W. Hutton; Peter M. Atkinson (Ambio, 2020)

Major trends in the land surface phenology (LSP) of Africa, controlling for land-cover change - Tracy Adole; Jadunandan Dash; Peter M. Atkinson (International Journal of Remote Sensing, 2018)

Large‐scale prerain vegetation green‐up across Africa - Tracy Adole; Jadunandan Dash; Peter M. Atkinson (Global Change Biology, 2018)
Information on the response of vegetation to different environmental drivers, including rainfall, forms a critical input to ecosystem models. Currently, such models are run based on parameters that, in some cases, are either assumed or lack supporting evidence (e.g., that vegetation growth across Africa is rainfall‐driven). A limited number of studies have reported that the onset of rain across Africa does not fully explain the onset of vegetation growth, for example, drawing on the observation of prerain flush effects in some parts of Africa. The spatial extent of this prerain green‐up effect, however, remains unknown, leaving a large gap in our understanding that may bias ecosystem modelling. This paper provides the most comprehensive spatial assessment to‐date of the magnitude and frequency of the different patterns of phenology response to rainfall across Africa and for different vegetation types. To define the relations between phenology and rainfall, we investigated the spatial variation in the difference, in number of days, between the start of rainy season ( SRS ) and start of vegetation growing season ( SOS ); and between the end of rainy season ( ERS ) and end of vegetation growing season ( EOS ). We reveal a much more extensive spread of prerain green‐up over Africa than previously reported, with prerain green‐up being the norm rather than the exception. We also show the relative sparsity of postrain green‐up, confined largely to the Sudano‐Sahel region. While the prerain green‐up phenomenon is well documented, its large spatial extent was not anticipated. Our results, thus, contrast with the widely held view that rainfall drives the onset and end of the vegetation growing season across Africa. Our findings point to a much more nuanced role of rainfall in Africa's vegetation growth cycle than previously thought, specifically as one of a set of several drivers, with important implications for ecosystem modelling.

Mapping paddy rice fields by applying machine learning algorithms to multi-temporal Sentinel-1A and Landsat data - Alex O. Onojeghuo; George A. Blackburn; Qunming Wang; Peter M. Atkinson; Daniel Kindred; Yuxin Miao (International Journal of Remote Sensing, 2018)

Climate change is predicted to alter the current pest status of Globodera pallida and G. rostochiensis in the United Kingdom - Laura M. Jones; Ann‐Kristin Koehler; Mirek Trnka; Jan Balek; Andrew J. Challinor; Howard J. Atkinson; Peter E. Urwin (Global Change Biology, 2017)
The potato cyst nematodes Globodera pallida and G. rostochiensis are economically important plant pathogens causing losses to UK potato harvests estimated at £50 m/ year. Implications of climate change on their future pest status have not been fully considered. Here, we report growth of female G. pallida and G. rostochiensis over the range 15 to 25°C. Females per plant and their fecundity declined progressively with temperatures above 17.5°C for G. pallida , whilst females per plant were optimal between 17.5 and 22.5°C for G. rostochiensis . Relative reproductive success with temperature was confirmed on two potato cultivars infected with either species at 15, 22.5 and 25°C. The reduced reproductive success of G. pallida at 22.5°C relative to 15°C was also recorded for a further seven host cultivars studied. The differences in optimal temperatures for reproductive success may relate to known differences in the altitude of their regions of origin in the Andes. Exposure of G. pallida to a diurnal temperature stress for one week during female growth significantly suppressed subsequent growth for one week at 17.5°C but had no effect on G. rostochiensis . However, after two weeks of recovery, female size was not significantly different from that for the control treatment. Future soil temperatures were simulated for medium‐ and high‐emission scenarios and combined with nematode growth data to project future implications of climate change for the two species. Increased soil temperatures associated with climate change may reduce the pest status of G. pallida but benefit G. rostochiensis especially in the southern United Kingdom. We conclude that plant breeders may be able to exploit the thermal limits of G. pallida by developing potato cultivars able to grow under future warm summer conditions. Existing widely deployed resistance to G. rostochiensis is an important characteristic to retain for new potato cultivars.

A multiple-point spatially weighted k -NN classifier for remote sensing - Yunwei Tang; Linhai Jing; Peter M. Atkinson; Hui Li (International Journal of Remote Sensing, 2016)

A novel multi-parameter support vector machine for image classification - Ce Zhang; Tiejun Wang; Peter M. Atkinson; Xin Pan; Huapeng Li (International Journal of Remote Sensing, 2015)

Elucidating the impact of temperature variability and extremes on cereal croplands through remote sensing - John M. A. Duncan; Jadunandan Dash; Peter M. Atkinson (Global Change Biology, 2015)
Remote sensing‐derived wheat crop yield‐climate models were developed to highlight the impact of temperature variation during thermo‐sensitive periods (anthesis and grain‐filling; TSP ) of wheat crop development. Specific questions addressed are: can the impact of temperature variation occurring during the TSP on wheat crop yield be detected using remote sensing data and what is the impact? Do crop critical temperature thresholds during TSP exist in real world cropping landscapes? These questions are tested in one of the world's major wheat breadbaskets of Punjab and Haryana, north‐west India. Warming average minimum temperatures during the TSP had a greater negative impact on wheat crop yield than warming maximum temperatures. Warming minimum and maximum temperatures during the TSP explain a greater amount of variation in wheat crop yield than average growing season temperature. In complex real world cereal croplands there was a variable yield response to critical temperature threshold exceedance, specifically a more pronounced negative impact on wheat yield with increased warming events above 35 °C. The negative impact of warming increases with a later start‐of‐season suggesting earlier sowing can reduce wheat crop exposure harmful temperatures. However, even earlier sown wheat experienced temperature‐induced yield losses, which, when viewed in the context of projected warming up to 2100 indicates adaptive responses should focus on increasing wheat tolerance to heat. This study shows it is possible to capture the impacts of temperature variation during the TSP on wheat crop yield in real world cropping landscapes using remote sensing data; this has important implications for monitoring the impact of climate change, variation and heat extremes on wheat croplands.

Pierre Dutilleul: Spatio-temporal Heterogeneity: Concepts and Analyses - Peter M. Atkinson (Mathematical Geosciences, 2014)

Exploring the spatio-temporal relationship between two key aeroallergens and meteorological variables in the United Kingdom - Nabaz Khwarahm; Jadunandan Dash; Peter M. Atkinson; R. M. Newnham; C. A. Skjøth; B. Adams-Groom; Eric Caulton; K. Head (International Journal of Biometeorology, 2014)

Ecological sustainability in rangelands: the contribution of remote sensing - Tal Svoray; Avi Perevolotsky; Peter M. Atkinson (International Journal of Remote Sensing, 2013)

Super-resolution mapping using Hopfield Neural Network with panchromatic imagery - Quang Minh Nguyen; Peter M. Atkinson; Hugh G. Lewis (International Journal of Remote Sensing, 2011)

A characterisation of climate variability and trends in hydrological extremes in the Severn Uplands - Eloise M. Biggs; Peter M. Atkinson (International Journal of Climatology, 2011)
Hydrological and climatic characteristics were investigated within the Severn Uplands to determine the interconnection between variables with a focus on understanding changes in hydrological extremes. Time series of precipitation and flows over a 30‐year period were analysed for trends in extremes. The Mann–Kendall (MK) non‐parametric test was used to detect trends at six rain gauges and five flow gauges across the catchment. Maxima, percentiles and N ‐day maxima of precipitation and flow distributions were investigated to identify changes in extreme intensity, frequency and persistence, respectively. Results indicated some significant statistical trends at annual, seasonal, and monthly scales. The largest number of significant trends in extreme precipitation was identified at mountainous gauge locations where significant increases in extreme precipitation persistence were detected annually and during spring and winter. Additionally, significant increases in extreme precipitation frequency were observed annually and during autumn and winter. Trends in flow identified an increase in extreme intensity on an annual basis, as well as during winter and the month of July, and a decrease in extreme frequency at certain stations during spring. Changes in climate variables were investigated to identify causal relationships with precipitation and flow hydrological extremes. Extremes were found to coincide with certain weather types, generally characteristic of cyclonic conditions and/or orographic enhancement. These were largely correlated with strong positive and negative stages of the North Atlantic oscillation, particularly during winter. Snow cover records indicated rapid decline in the Severn Uplands and a reduction in snow indicated a link to changes in spring hydrological extremes. All changes seemed to be driven by the underlying climate variable of air temperature, which coincided with changes in observed national and global temperature records. Hydroclimatological changes indicated a possible temporal shift in the occurrence of extreme hydrological events, which was likely to have been affected by changes in catchment physical properties. Copyright © 2010 Royal Meteorological Society

The Why, What, and How of Global Biodiversity Indicators Beyond the 2010 Target - JULIA P. G. JONES; BEN COLLEN; GILES ATKINSON; PETER W. J. BAXTER; PHILIP BUBB; JANINE B. ILLIAN; TODD E. KATZNER; AIDAN KEANE; JONATHAN LOH; EVE MCDONALD‐MADDEN; EMILY NICHOLSON; HENRIQUE M. PEREIRA; et al. (Conservation Biology, 2011)
The 2010 biodiversity target agreed by signatories to the Convention on Biological Diversity directed the attention of conservation professionals toward the development of indicators with which to measure changes in biological diversity at the global scale. We considered why global biodiversity indicators are needed, what characteristics successful global indicators have, and how existing indicators perform. Because monitoring could absorb a large proportion of funds available for conservation, we believe indicators should be linked explicitly to monitoring objectives and decisions about which monitoring schemes deserve funding should be informed by predictions of the value of such schemes to decision making. We suggest that raising awareness among the public and policy makers, auditing management actions, and informing policy choices are the most important global monitoring objectives. Using four well‐developed indicators of biological diversity (extent of forests, coverage of protected areas, Living Planet Index, Red List Index) as examples, we analyzed the characteristics needed for indicators to meet these objectives. We recommend that conservation professionals improve on existing indicators by eliminating spatial biases in data availability, fill gaps in information about ecosystems other than forests, and improve understanding of the way indicators respond to policy changes. Monitoring is not an end in itself, and we believe it is vital that the ultimate objectives of global monitoring of biological diversity inform development of new indicators.

Exploring the impact of climate and land use changes on streamflow trends in a monsoon catchment - Nor Aizam Adnan; Peter M. Atkinson (International Journal of Climatology, 2011)
Flooding appears to be increasing in Kelantan, Malaysia, in terms of frequency as well as magnitude. This is likely to be due to changes in precipitation, but may also be contributed to by land use change. The Mann–Kendall non‐parametric method was used to test for trends in streamflow and precipitation at the 90% significance level. Several significant trends in streamflow were found for the upstream (River Galas) and downstream (River Kelantan) sub‐catchments for all variables (annual, seasonal and monthly time‐series). In particular, streamflow increased in all seasons in the upstream sub‐catchment, but increased in the wet season and decreased in the dry season downstream. Several trends were also observed for precipitation. Precipitation trends were increasing in the wet season and decreasing in the dry season for both upstream and downstream sub‐catchments. Analysis of land use change revealed that most changes occurred through conversion of forest to agricultural land (i.e. rubber and oil palm), predominantly in the upstream sub‐catchment. The analysis suggests a clear association between streamflow change and precipitation change, but also reveals that land use change may be an important contributing factor, particularly in the upstream sub‐catchment. Copyright © 2010 Royal Meteorological Society

Microphthalmia, parkinsonism, and enhanced nociception in Pitx3 416insG mice - Michael Rosemann; Alesia Ivashkevich; Jack Favor; Claudia Dalke; Sabine M. Hölter; Lore Becker; Ildikó Rácz; Ines Bolle; Martina Klempt; Birgit Rathkolb; Svetoslav Kalaydjiev; Thure Adler; et al. (Mammalian Genome, 2010)

Issues of uncertainty in super-resolution mapping and their implications for the design of an inter-comparison study - Peter M. Atkinson (International Journal of Remote Sensing, 2009)

Transgenic Arabidopsis leaf tissue expressing a modified oryzacystatin shows resistance to the field slug Deroceras reticulatum (Müller) - Anthony J. Walker; Peter E. Urwin; Howard J. Atkinson; Philip Brain; David M. Glen; Peter R. Shewry (Transgenic Research, 1999)

Radiometric dating of the Middle Palaeolithic tool industry and associated fauna of Pin Hole Cave, Creswell Crags, England - Roger M. Jacobi; Peter J. Rowe; Mabs A. Gilmour; Rainer Grün; Timothy C. Atkinson (Journal of Quaternary Science, 1998)

Radiometric dating of the Middle Palaeolithic tool industry and associated fauna of Pin Hole Cave, Creswell Crags, England - Roger M. Jacobi; Peter J. Rowe; Mabs A. Gilmour; Rainer Grün; Timothy C. Atkinson (Journal of Quaternary Science, 1998)