All Outputs (99)

Informing action for United Nations SDG target 8.7 and interdependent SDGs: Examining modern slavery from space (2021)
Journal Article
Boyd, D. S., Perrat, B., Li, X., Jackson, B., Landman, T., Ling, F., …Foody, G. M. (2021). Informing action for United Nations SDG target 8.7 and interdependent SDGs: Examining modern slavery from space. Humanities and Social Sciences Communications, 8, Article 111. https://doi.org/10.1057/s41599-021-00792-z

This article provides an example of the ways in which remote sensing, Earth observation, and machine learning can be deployed to provide the most up to date quantitative portrait of the South Asian ‘Brick Belt’, with a view to understanding the exten... Read More about Informing action for United Nations SDG target 8.7 and interdependent SDGs: Examining modern slavery from space.

Tracking small-scale tropical forest disturbances: Fusing the Landsat and Sentinel-2 data record (2021)
Journal Article
Zhang, Y., Ling, F., Wang, X., Foody, G. M., Boyd, D. S., Li, X., …Atkinson, P. M. (2021). Tracking small-scale tropical forest disturbances: Fusing the Landsat and Sentinel-2 data record. Remote Sensing of Environment, 261, Article 112470. https://doi.org/10.1016/j.rse.2021.112470

Information on forest disturbance is crucial for tropical forest management and global carbon cycle analysis. The long-term collection of data from the Landsat missions provides some of the most valuable information for understanding the processes of... Read More about Tracking small-scale tropical forest disturbances: Fusing the Landsat and Sentinel-2 data record.

rasterdiv—An Information Theory tailored R package for measuring ecosystem heterogeneity from space: To the origin and back (2021)
Journal Article
Rocchini, D., Thouverai, E., Marcantonio, M., Iannacito, M., Da Re, D., Torresani, M., …Wegmann, M. (2021). rasterdiv—An Information Theory tailored R package for measuring ecosystem heterogeneity from space: To the origin and back. Methods in Ecology and Evolution, 12(6), 1093-1102. https://doi.org/10.1111/2041-210X.13583

Ecosystem heterogeneity has been widely recognized as a key ecological indicator of several ecological functions, diversity patterns and change, metapopulation dynamics, population connectivity or gene flow. In this paper, we present a new R package—... Read More about rasterdiv—An Information Theory tailored R package for measuring ecosystem heterogeneity from space: To the origin and back.

Impacts of ignorance on the accuracy of image classification and thematic mapping (2021)
Journal Article
Foody, G. M. (2021). Impacts of ignorance on the accuracy of image classification and thematic mapping. Remote Sensing of Environment, 259, Article 112367. https://doi.org/10.1016/j.rse.2021.112367

Thematic maps are often derived from remotely sensed imagery via a supervised image classification analysis. The training and testing stages of a supervised image classification may proceed ignorant of the presence of some classes in the region to be... Read More about Impacts of ignorance on the accuracy of image classification and thematic mapping.

Remote sensing liana infestation in an aseasonal tropical forest: addressing mismatch in spatial units of analyses (2021)
Journal Article
Chandler, C. J., Van Der Heijden, G. M. F., Boyd, D. S., Cutler, M. E. J., Costa, H., Nilus, R., & Foody, G. M. (2021). Remote sensing liana infestation in an aseasonal tropical forest: addressing mismatch in spatial units of analyses. Remote Sensing in Ecology and Conservation, https://doi.org/10.1002/rse2.197

The ability to accurately assess liana (woody vine) infestation at the landscape level is essential to quantify their impact on carbon dynamics and help inform targeted forest management and conservation action. Remote sensing techniques provide pote... Read More about Remote sensing liana infestation in an aseasonal tropical forest: addressing mismatch in spatial units of analyses.

Scrutinizing relationships between submarine groundwater discharge and upstream areas using thermal remote sensing: A case study in the northern Persian gulf (2021)
Journal Article
Samani, A. N., Farzin, M., Rahmati, O., Feiznia, S., Kazemi, G. A., Foody, G., & Melesse, A. M. (2021). Scrutinizing relationships between submarine groundwater discharge and upstream areas using thermal remote sensing: A case study in the northern Persian gulf. Remote Sensing, 13(3), https://doi.org/10.3390/rs13030358

© 2021 by the authors. Licensee MDPI, Basel, Switzerland. Nutrient input through submarine groundwater discharge (SGD) often plays a significant role in primary productivity and nutrient cycling in the coastal areas. Understanding relationships betwe... Read More about Scrutinizing relationships between submarine groundwater discharge and upstream areas using thermal remote sensing: A case study in the northern Persian gulf.

Comparison of simple averaging and latent class modeling to estimate the area of land cover in the presence of reference data variability (2021)
Journal Article
Xing, D., Stehman, S. V., Foody, G. M., & Pengra, B. W. (2021). Comparison of simple averaging and latent class modeling to estimate the area of land cover in the presence of reference data variability. Land, 10(1), Article 35. https://doi.org/10.3390/land10010035

© 2021 by the authors. Licensee MDPI, Basel, Switzerland. Estimates of the area or percent area of the land cover classes within a study region are often based on the reference land cover class labels assigned by analysts interpreting satellite image... Read More about Comparison of simple averaging and latent class modeling to estimate the area of land cover in the presence of reference data variability.

Object-Based Area-to-Point Regression Kriging for Pansharpening (2020)
Journal Article
Zhang, Y., Atkinson, P. M., Ling, F., Foody, G. M., Wang, Q., Ge, Y., …Du, Y. (2021). Object-Based Area-to-Point Regression Kriging for Pansharpening. IEEE Transactions on Geoscience and Remote Sensing, 59(10), 8599-8614. https://doi.org/10.1109/TGRS.2020.3041724

IEEE Optical earth observation satellite sensors often provide a coarse spatial resolution (CR) multispectral (MS) image together with a fine spatial resolution (FR) panchromatic (PAN) image. Pansharpening is a technique applied to such satellite sen... Read More about Object-Based Area-to-Point Regression Kriging for Pansharpening.

Let your maps be fuzzy!—Class probabilities and floristic gradients as alternatives to crisp mapping for remote sensing of vegetation (2020)
Journal Article
Feilhauer, H., Zlinszky, A., Kania, A., Foody, G. M., Doktor, D., Lausch, A., & Schmidtlein, S. (2020). Let your maps be fuzzy!—Class probabilities and floristic gradients as alternatives to crisp mapping for remote sensing of vegetation. Remote Sensing in Ecology and Conservation, https://doi.org/10.1002/rse2.188

© 2020 The Authors. Remote Sensing in Ecology and Conservation published by John Wiley & Sons Ltd on behalf of Zoological Society of London. Mapping vegetation as hard classes based on remote sensing data is a frequently applied approach, even thou... Read More about Let your maps be fuzzy!—Class probabilities and floristic gradients as alternatives to crisp mapping for remote sensing of vegetation.

Investigating the potential of radar interferometry for monitoring rural artisanal cobalt mines in the democratic republic of the congo (2020)
Journal Article
Brown, C., Daniels, A., Boyd, D. S., Sowter, A., Foody, G., & Kara, S. (2020). Investigating the potential of radar interferometry for monitoring rural artisanal cobalt mines in the democratic republic of the congo. Sustainability, 12(23), Article 9834. https://doi.org/10.3390/su12239834

© 2020 by the authors. Licensee MDPI, Basel, Switzerland. Greater awareness of the serious human rights abuses associated with the extraction and trade of cobalt in the Democratic Republic of the Congo (DRC) has applied increasing pressure for busine... Read More about Investigating the potential of radar interferometry for monitoring rural artisanal cobalt mines in the democratic republic of the congo.

Cloud detection in Landsat-8 imagery in Google Earth Engine based on a deep convolutional neural network (2020)
Journal Article
Yin, Z., Ling, F., Foody, G. M., Li, X., & Du, Y. (2020). Cloud detection in Landsat-8 imagery in Google Earth Engine based on a deep convolutional neural network. Remote Sensing Letters, 11(12), 1181-1190. https://doi.org/10.1080/2150704X.2020.1833096

© 2020 Informa UK Limited, trading as Taylor & Francis Group. Google Earth Engine (GEE) provides a convenient platform for applications based on optical satellite imagery of large areas. With such data sets, the detection of cloud is often a necess... Read More about Cloud detection in Landsat-8 imagery in Google Earth Engine based on a deep convolutional neural network.

Remote sensing of fish-processing in the Sundarbans Reserve Forest, Bangladesh: an insight into the modern slavery-environment nexus in the coastal fringe (2020)
Journal Article
Jackson, B., Boyd, D. S., Ives, C. D., Decker Sparks, J. L., Foody, G. M., Marsh, S., & Bales, K. (2020). Remote sensing of fish-processing in the Sundarbans Reserve Forest, Bangladesh: an insight into the modern slavery-environment nexus in the coastal fringe. Maritime Studies, 19(4), 429–444. https://doi.org/10.1007/s40152-020-00199-7

© 2020, The Author(s). Land-based fish-processing activities in coastal fringe areas and their social-ecological impacts have often been overlooked by marine scientists and antislavery groups. Using remote sensing methods, the location and impacts of... Read More about Remote sensing of fish-processing in the Sundarbans Reserve Forest, Bangladesh: an insight into the modern slavery-environment nexus in the coastal fringe.

Superresolution Land Cover Mapping Using a Generative Adversarial Network (2020)
Journal Article
Shang, C., Li, X., Foody, G. M., Du, Y., & Ling, F. (2022). Superresolution Land Cover Mapping Using a Generative Adversarial Network. IEEE Geoscience and Remote Sensing Letters, 19, Article 6000105. https://doi.org/10.1109/LGRS.2020.3020395

Superresolution mapping (SRM) is a commonly used method to cope with the problem of mixed pixels when predicting the spatial distribution within low-resolution pixels. Central to the popular SRM method is the spatial pattern model, which is utilized... Read More about Superresolution Land Cover Mapping Using a Generative Adversarial Network.

Monitoring surface water area variations of reservoirs using daily MODIS images by exploring sub-pixel information (2020)
Journal Article
Ling, F., Li, X., Foody, G. M., Boyd, D., Ge, Y., Li, X., & Du, Y. (2020). Monitoring surface water area variations of reservoirs using daily MODIS images by exploring sub-pixel information. ISPRS Journal of Photogrammetry and Remote Sensing, 168, 141-152. https://doi.org/10.1016/j.isprsjprs.2020.08.008

© 2020 International Society for Photogrammetry and Remote Sensing, Inc. (ISPRS) Information on the temporal variation of surface water area of reservoirs is fundamental for water resource management and is often monitored by satellite remote sensing... Read More about Monitoring surface water area variations of reservoirs using daily MODIS images by exploring sub-pixel information.

Active restoration accelerates the carbon recovery of human-modified tropical forests (2020)
Journal Article
Philipson, C. D., Cutler, M. E. J., Brodrick, P. G., Asner, G. P., Boyd, D. S., Costa, P. M., …Burslem, D. F. R. P. (2020). Active restoration accelerates the carbon recovery of human-modified tropical forests. Science, 369(6505), 838-841. https://doi.org/10.1126/science.aay4490

More than half of all tropical forests are degraded by human impacts, leaving them threatened with conversion to agricultural plantations and risking substantial biodiversity and carbon losses. Restoration could accelerate recovery of aboveground car... Read More about Active restoration accelerates the carbon recovery of human-modified tropical forests.

Spatiotemporal Fusion of Land Surface Temperature Based on a Convolutional Neural Network (2020)
Journal Article
Yin, Z., Wu, P., Foody, G. M., Wu, Y., Liu, Z., Du, Y., & Ling, F. (2021). Spatiotemporal Fusion of Land Surface Temperature Based on a Convolutional Neural Network. IEEE Transactions on Geoscience and Remote Sensing, 59(2), 1808-1822. https://doi.org/10.1109/TGRS.2020.2999943

© 1980-2012 IEEE. Due to the tradeoff between spatial and temporal resolutions commonly encountered in remote sensing, no single satellite sensor can provide fine spatial resolution land surface temperature (LST) products with frequent coverage. This... Read More about Spatiotemporal Fusion of Land Surface Temperature Based on a Convolutional Neural Network.

Iterative Training Sample Expansion to Increase and Balance the Accuracy of Land Classification from VHR Imagery (2020)
Journal Article
Lv, Z., Li, G., Jin, Z., Benediktsson, J. A., & Foody, G. M. (2021). Iterative Training Sample Expansion to Increase and Balance the Accuracy of Land Classification from VHR Imagery. IEEE Transactions on Geoscience and Remote Sensing, 59(1), 139-150. https://doi.org/10.1109/TGRS.2020.2996064

© 1980-2012 IEEE. Imbalanced training sets are known to produce suboptimal maps for supervised classification. Therefore, one challenge in mapping land cover is acquiring training data that will allow classification with high overall accuracy (OA) in... Read More about Iterative Training Sample Expansion to Increase and Balance the Accuracy of Land Classification from VHR Imagery.

Use of automated change detection and VGI sources for identifying and validating urban land use change (2020)
Journal Article
Olteanu-Raimond, A. M., See, L., Schultz, M., Foody, G., Riffler, M., Gasber, T., …Gombert, M. (2020). Use of automated change detection and VGI sources for identifying and validating urban land use change. Remote Sensing, 12(7), Article 1186. https://doi.org/10.3390/rs12071186

© 2020, by the authors. Land use and land cover (LULC) mapping is often undertaken by national mapping agencies, where these LULC products are used for different types of monitoring and reporting applications. Updating of LULC databases is often done... Read More about Use of automated change detection and VGI sources for identifying and validating urban land use change.

Spatio-temporal sub-pixel land cover mapping of remote sensing imagery using spatial distribution information from same-class pixels (2020)
Journal Article
Li, X., Chen, R., Foody, G. M., Wang, L., Yang, X., Du, Y., & Ling, F. (2020). Spatio-temporal sub-pixel land cover mapping of remote sensing imagery using spatial distribution information from same-class pixels. Remote Sensing, 12(3), Article 503. https://doi.org/10.3390/rs12030503

© 2020 by the authors. The generation of land cover maps with both fine spatial and temporal resolution would aid the monitoring of change on the Earth's surface. Spatio-temporal sub-pixel land cover mapping (STSPM) uses a few fine spatial resolution... Read More about Spatio-temporal sub-pixel land cover mapping of remote sensing imagery using spatial distribution information from same-class pixels.

Explaining the unsuitability of the kappa coefficient in the assessment and comparison of the accuracy of thematic maps obtained by image classification (2020)
Journal Article
Foody, G. M. (2020). Explaining the unsuitability of the kappa coefficient in the assessment and comparison of the accuracy of thematic maps obtained by image classification. Remote Sensing of Environment, 239, https://doi.org/10.1016/j.rse.2019.111630

The kappa coefficient is not an index of accuracy, indeed it is not an index of overall agreement but one of agreement beyond chance. Chance agreement is, however, irrelevant in an accuracy assessment and is anyway inappropriately modelled in the cal... Read More about Explaining the unsuitability of the kappa coefficient in the assessment and comparison of the accuracy of thematic maps obtained by image classification.