All Outputs (107)

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., Fiddes, J., Foody, G. M., Van Der Heijden, G. M., Ledo, A., Lincoln, P. R., Margrove, J. A., Martin, R. E., Milne, S., Pinard, M. A., Reynolds, G., Snoep, M., Tangki, H., Wai, Y. S., Wheeler, C. E., & 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., Jolivet, L., le Bris, A., Meneroux, Y., Liu, L., Poupée, M., & 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, Article 111630. 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.

SFSDAF: an enhanced FSDAF that incorporates sub-pixel class fraction change information for spatio-temporal image fusion (2019)
Journal Article
Li, X., Foody, G. M., Boyd, D. S., Ge, Y., Zhang, Y., Du, Y., & Ling, F. (2020). SFSDAF: an enhanced FSDAF that incorporates sub-pixel class fraction change information for spatio-temporal image fusion. Remote Sensing of Environment, 237, Article 111537. https://doi.org/10.1016/j.rse.2019.111537

Spatio-temporal image fusion methods have become a popular means to produce remotely sensed data sets that have both fine spatial and temporal resolution. Accurate prediction of reflectance change is difficult, especially when the change is caused by... Read More about SFSDAF: an enhanced FSDAF that incorporates sub-pixel class fraction change information for spatio-temporal image fusion.

Night-time lights are more strongly related to urban building volume than to urban area (2019)
Journal Article
Shi, L., Foody, G. M., Boyd, D. S., Girindran, R., Wang, L., Du, Y., & Ling, F. (2020). Night-time lights are more strongly related to urban building volume than to urban area. Remote Sensing Letters, 11(1), 29-36. https://doi.org/10.1080/2150704X.2019.1682709

A strong relationship between night-time light (NTL) data and the areal extent of urbanized regions has been observed frequently. As urban regions have an important vertical dimension, it is hypothesized that the strength of the relationship with NTL... Read More about Night-time lights are more strongly related to urban building volume than to urban area.

Measuring River Wetted Width from Remotely Sensed Imagery at the Subpixel Scale with a Deep Convolutional Neural Network (2019)
Journal Article
Ling, F., Boyd, D., Ge, Y., Foody, G. M., Li, X., Wang, L., Zhang, Y., Shi, L., Shang, C., Li, X., & Du, Y. (2019). Measuring River Wetted Width from Remotely Sensed Imagery at the Subpixel Scale with a Deep Convolutional Neural Network. Water Resources Research, 55(7), 5631-5649. https://doi.org/10.1029/2018wr024136

River wetted width (RWW) is an important variable in the study of river hydrological and biogeochemical processes. Presently, RWW is often measured from remotely sensed imagery and the accuracy of RWW estimation is typically low when coarse spatial r... Read More about Measuring River Wetted Width from Remotely Sensed Imagery at the Subpixel Scale with a Deep Convolutional Neural Network.

The World's Tallest Tropical Tree in Three Dimensions (2019)
Journal Article
Shenkin, A., Chandler, C. J., Boyd, D. S., Jackson, T., Disney, M., Majalap, N., Nilus, R., Foody, G., bin Jami, J., Reynolds, G., Wilkes, P., Cutler, M. E. J., van der Heijden, G. M. F., Burslem, D. F. R. P., Coomes, D. A., Bentley, L. P., & Malhi, Y. (2019). The World's Tallest Tropical Tree in Three Dimensions. Frontiers in Forests and Global Change, 2, 1-5. https://doi.org/10.3389/ffgc.2019.00032

Here we report the recent discovery of the world's tallest tropical tree (Shorea faguetiana), possibly the world's tallest angiosperm (flowering plant), located in the rainforests of Sabah, Malaysian Borneo. In addition, we provide a novel three-dime... Read More about The World's Tallest Tropical Tree in Three Dimensions.

Key issues in rigorous accuracy assessment of land cover products (2019)
Journal Article
Stehman, S. V., & Foody, G. M. (2019). Key issues in rigorous accuracy assessment of land cover products. Remote Sensing of Environment, 231, Article 111199. https://doi.org/10.1016/j.rse.2019.05.018

© 2019 Accuracy assessment and land cover mapping have been inexorably linked throughout the first 50 years of publication of Remote Sensing of Environment. The earliest developers of land-cover maps recognized the importance of evaluating the qualit... Read More about Key issues in rigorous accuracy assessment of land cover products.

Permanent disappearance and seasonal fluctuation of urban lake area in Wuhan, China monitored with long time series remotely sensed images from 1987 to 2016 (2019)
Journal Article
Shi, L., Ling, F., Foody, G. M., Chen, C., Fang, S., Li, X., Zhang, Y., & Du, Y. (2019). Permanent disappearance and seasonal fluctuation of urban lake area in Wuhan, China monitored with long time series remotely sensed images from 1987 to 2016. International Journal of Remote Sensing, 40(22), 1-22. https://doi.org/10.1080/01431161.2019.1612119

Lakes are important to the healthy functioning of the urban ecosystem. The urban lakes in Wuhan, China, which is known as ‘city of hundreds of lakes’, are facing substantial threats mainly due to rapid urbanization. This paper focused on detecting th... Read More about Permanent disappearance and seasonal fluctuation of urban lake area in Wuhan, China monitored with long time series remotely sensed images from 1987 to 2016.

Spatial-temporal super-resolution land cover mapping with a local spatial-temporal dependence model (2019)
Journal Article
Li, X., Ling, F., Foody, G. M., Ge, Y., Zhang, Y., Wang, L., Shi, L., Li, X., & Du, Y. (2019). Spatial-temporal super-resolution land cover mapping with a local spatial-temporal dependence model. IEEE Transactions on Geoscience and Remote Sensing, 57(7), 4951-4966. https://doi.org/10.1109/TGRS.2019.2894773

The mixed pixel problem is common in remote sensing. A soft classification can generate land cover class fraction images that illustrate the areal proportions of the various land cover classes within pixels. The spatial distribution of land cover cla... Read More about Spatial-temporal super-resolution land cover mapping with a local spatial-temporal dependence model.

Super-resolution land cover mapping by deep learning (2019)
Journal Article
Ling, F., & Foody, G. M. (2019). Super-resolution land cover mapping by deep learning. Remote Sensing Letters, 10(6), 598-606. https://doi.org/10.1080/2150704x.2019.1587196

Super-resolution mapping (SRM) is a technique to estimate a fine spatial resolution land cover map from coarse spatial resolution fractional proportion images. SRM is often based explicitly on the use of a spatial pattern model that represents the la... Read More about Super-resolution land cover mapping by deep learning.

Optimal endmember-based super-resolution land cover mapping (2019)
Journal Article
Li, X., Li, X., Foody, G., Yang, X., Zhang, Y., Du, Y., & Ling, F. (2019). Optimal endmember-based super-resolution land cover mapping. IEEE Geoscience and Remote Sensing Letters, 16(8), 1279-1283. https://doi.org/10.1109/lgrs.2019.2894805

Super-resolution mapping (SRM) aims to determine the spatial distribution of the land cover classes contained in the area represented by mixed pixels to obtain a more appropriate and accurate map at a finer spatial resolution than the input remotely... Read More about Optimal endmember-based super-resolution land cover mapping.

Earth observation and machine learning to meet Sustainable Development Goal 8.7: mapping sites associated with slavery from space (2019)
Journal Article
Foody, G., Ling, F., Boyd, D., Li, X., & Wardlaw, J. (2019). Earth observation and machine learning to meet Sustainable Development Goal 8.7: mapping sites associated with slavery from space. Remote Sensing, 11(3), Article 266. https://doi.org/10.3390/rs11030266

A large proportion of the workforce in the brick kilns of the Brick Belt of Asia are modern-day slaves. Work to liberate slaves and contribute to UN Sustainable Development Goal 8.7 would benefit from maps showing the location of brick kilns. Previou... Read More about Earth observation and machine learning to meet Sustainable Development Goal 8.7: mapping sites associated with slavery from space.

Exploring temporality in socio-ecological resilience through experiences of the 2015/16 El Niño across the tropics (2019)
Journal Article
Whitfield, S., Beauchamp, E., Boyd, D. S., Burslem, D., Byg, A., Colledge, F., Cutler, M., Didena, M., Dougill, A., Foody, G., Godbold, J. A., Hazenbosch, M., Hirons, M., Speranza, I. C., Jew, E., Lacambra, C., Mkwambisi, D., Moges, A., Morel, A., Morris, R., …White, P. C. (2019). Exploring temporality in socio-ecological resilience through experiences of the 2015/16 El Niño across the tropics. Global Environmental Change, 55, 1-14. https://doi.org/10.1016/j.gloenvcha.2019.01.004

In a context of both long-term climatic changes and short-term climatic shocks, temporal dynamics profoundly influence ecosystems and societies. In low income contexts in the Tropics, where both exposure and vulnerability to climatic fluctuations is... Read More about Exploring temporality in socio-ecological resilience through experiences of the 2015/16 El Niño across the tropics.

Reducing the impacts of intra-class spectral variability on the accuracy of soft classification and super-resolution mapping of shoreline (2018)
Journal Article
Doan, H. T., Foody, G. M., & Bui, D. T. (2019). Reducing the impacts of intra-class spectral variability on the accuracy of soft classification and super-resolution mapping of shoreline. International Journal of Remote Sensing, 40(9), 3384-3400. https://doi.org/10.1080/01431161.2018.1545099

The main objective of this research is to assess the impact of intra-class spectral variation on the accuracy of soft classification and super-resolution mapping. The accuracy of both analyses was negatively related to the degree of intra-class spect... Read More about Reducing the impacts of intra-class spectral variability on the accuracy of soft classification and super-resolution mapping of shoreline.