Published Articles by Daniel Donoghue
Remote Sensing, 2018
We present a novel approach that uses remote sensing to record and reconstruct traces of ancient ... more We present a novel approach that uses remote sensing to record and reconstruct traces of ancient water management throughout the whole region of Northern Mesopotamia, an area where modern agriculture and warfare has had a severe impact on the survival of archaeological remains and their visibility in modern satellite imagery. However, analysis and interpretation of declassified stereoscopic spy satellite data from the 1960s and early 1970s revealed traces of ancient water management systems. We processed satellite imagery to facilitate image interpretation and used photogrammetry to reconstruct hydraulic pathways. Our results represent the first comprehensive map of water management features across the entirety of Northern Mesopotamia for the period ca. 1200 BC to AD 1500. In particular, this shows that irrigation was widespread throughout the region in the Early Islamic period, including within the zone traditionally regarded as "rain-fed". However, we found that a high proportion of the ancient canal systems had been damaged or destroyed by 20th century changes to agricultural practices and land use. Given this, there is an urgent need to record these rapidly vanishing water management systems that were an integral part of the ancient agricultural landscape and that underpinned powerful states.
Papers by Daniel Donoghue
Biomass estimation in mangrove forests: a comparison of allometric models incorporating species and structural information
Zenodo (CERN European Organization for Nuclear Research), Oct 31, 2021
Improved estimates of aboveground biomass (AGB) are required to improve our understanding of the ... more Improved estimates of aboveground biomass (AGB) are required to improve our understanding of the productivity of mangrove forests to support the long-term conservation of these fragile ecosystems which are under threat from many natural and anthropogenic pressures. To understand how individual species affects biomass estimates in mangrove forests, five species-specific and four genus-specific allometric models were developed. Independent tree inventory data were collected from 140 sample plots to compare the AGB among the species-specific models and seven frequently used pan-tropical and Sundarbans-specific generic models. The effect of individual tree species was also evaluated using model parameters for wood densities (from individual trees to the whole Sundarbans) and tree heights (individual, plot average and plot top height). All nine developed models explained a high percentage of the variance in tree AGB (R 2 = 0.97–0.99) with the diameter at breast height and total height (H). At the individual tree level, the generic allometric models overestimated AGB from 22% to 167% compared to the species-specific models. At the plot level, mean AGB varied from 111.36 Mg ha−1 to 299.48 Mg ha−1, where AGB significantly differed in all generic models compared to the species-specific models (p < 0.05). Using measured species wood density (WD) in the allometric model showed 4.5%–9.7% less biomass than WD from published databases and other sources. When using plot top height and plot average height rather than measured individual tree height, the AGB was overestimated by 19.5% and underestimated by 8.3% (p < 0.05). The study demonstrates that species-specific allometric models and individual tree measurements benefit biomass estimation in mangrove forests. Tree level measurement from the inventory plots, if available, should be included in allometric models to improve the accuracy of forest biomass estimates, particularly when upscaling individual trees up to the ecosystem level.
Remote sensing & GIS for coastal habitat mapping & monitoring [DvD] (Joint IOC-IOI training course on remote sensing for coastal and ocean management, September 2006)
Applications of remote sensing & GIS Part II [DvD] (Joint IOC-IOI training course on remote sensing and GIS for coastal and ocean management, September 2006)
Archaeological Remote Sensing
The application of remote sensing to environmental archaeology
Geoarchaeology-an International Journal, 1988
ABSTRACT An area in the Fenlands of Eastern England was used to assess the spectral, spatial, and... more ABSTRACT An area in the Fenlands of Eastern England was used to assess the spectral, spatial, and seasonal requirements of airborne multispectral data for identifying wetland archaeological features by detecting crop and soil marks. Ordination of data from a scanner with 11 spectral channels was achieved using the Sheffield method, which calculates the wavebands that produce a 3 band composite image with optimum contrast using band variances and interband correlations. the spatial detail requirements for multispectral data were investigated by applying an edge enhancing filter to single waveband images. the loss of feature clarity with increased levels of spatial smoothing is visually apparent. Seasonal variation in crop mark visibility was quantified by cross tabulating feature visibility in fields known to contain features with time period and sensor type.If remote sensing is to be used for repeated operational archaeological survey then the quality and quantity of information which can be gained from the data must be evaluated. This study attempts to define some of the necessary operational requirements for the use of multispectral data for archaeology.
Special Issue ForestSat 2007
HAL (Le Centre pour la Communication Scientifique Directe), 2009
Mapping and monitoring the intertidal zone of the East coast of England using remote sensing techniques and a coastal monitoring GIS
Marine Technology Society Journal, 1994
The paper compares two different techniques for mapping the intertidal zone of the Wash estuary o... more The paper compares two different techniques for mapping the intertidal zone of the Wash estuary on the East coast of the United Kingdom using Landsat 5 thematic mapper (TM) satellite imagery. Two scenes from different dates were processed using a conventional maximum likelihood classifier and a fully constrained linear mixture model. The Landsat TM data was atmospherically and radiometrically corrected to allow meaningful comparison to be made between the scenes. The data were geometrically rectified and incorporated into a coastal monitoring Geographical Information System (GIS) along with information acquired from previous ground based surveys. -from Authorslink_to_subscribed_fulltex
Remote sensing
Progress in Physical Geography, Jun 1, 1999
This is a particularly exciting and tense time for remote-sensing science. The successful launch ... more This is a particularly exciting and tense time for remote-sensing science. The successful launch of the SeaWifs sensor in August 1997 gave an important boost to the oceanographic community with the first instrument purpose built for marine science since the Coastal Zone Colour Scanner. The MODIS sensor should follow SeaWifs on EOS-AM1 and IRS-P4 (Oceansat-1) some time in 1999. The study of global land cover and vegetation change will be enhanced with data from the VEGETATION sensor on SPOT4 that was launched in March 1998 (Eastwood et al., 1998). The first polar platform, part of NASA’s Earth Observation System, EOS-AM1, has had its launch delayed again but should be operational in 1999 (Kaufman et al., 1998). Landsat 7 is due for launch in April 1999 and with it comes the enhanced thematic mapper sensor (ETM+), a new pricing structure and a data policy that is designed to support the development of the commercial market (Landsat7 data policy 1997). The launches of the IKONOS and OrbView-3 sub-1m resolution digital imaging systems have been postponed from 1998 to 1999. Therefore, the coming months should herald an explosion of new data sets and scientific developments to add to the significant advances that have been reported in the scientific literature over the past 12 months.
Improving above ground biomass estimates of Southern Africa dryland forests by combining Sentinel-1 SAR and Sentinel-2 multispectral imagery
Remote Sensing of Environment
Planet, 2002
The Department of Geography at the University of Durham was one of three departments to pilot duo... more The Department of Geography at the University of Durham was one of three departments to pilot duo (Durham University Online) in October 2000. duo is the University's web-based learning environment. (), which uses the commercial product Blackboard (). Evaluations of the use of duo were undertaken within the Department of Geography at the beginning of the academic year in 2000 and across the whole University in April/May 2001. The success of duo with first-year undergraduates and with staff in the Geography Department has resulted in its use being extended to all second-year modules. This has also encouraged other departments to embed duo within their teaching. The article will hopefully be of interest to other GEES departments who might be considering delivering their curricula through an electronic learning environment.
Using Multi-Resolution and Multi-Temporal Imagery to Validate Tropical Forest Degradation
Remote sensing for monitoring tropical dryland forests: a review of current research, knowledge gaps and future directions for Southern Africa
Environmental Research Communications, 2022
Climate change, manifest via rising temperatures, extreme drought, and associated anthropogenic a... more Climate change, manifest via rising temperatures, extreme drought, and associated anthropogenic activities, has a negative impact on the health and development of tropical dryland forests. Southern Africa encompasses significant areas of dryland forests that are important to local communities but are facing rapid deforestation and are highly vulnerable to biome degradation from land uses and extreme climate events. Appropriate integration of remote sensing technologies helps to assess and monitor forest ecosystems and provide spatially explicit, operational, and long-term data to assist the sustainable use of tropical environment landscapes. The period from 2010 onwards has seen the rapid development of remote sensing research on tropical forests, which has led to a significant increase in the number of scientific publications. This review aims to analyse and synthesise the evidence published in peer review studies with a focus on optical and radar remote sensing of dryland forests ...
Environmental Research Letters, Nov 15, 2021
Ecological Informatics, 2018
The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, Feb 14, 2020
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Published Articles by Daniel Donoghue
Papers by Daniel Donoghue