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Tim Van de Voorde
Sino-Belgian Joint Laboratory for Geo-Information, 9000 Ghent, Belgium

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Journal article
Published: 13 August 2021 in Remote Sensing
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The spatial calculation of vector data is crucial for geochemical analysis in geological big data. However, large volumes of geochemical data make for inefficient management. Therefore, this study proposed a shapefile storage method based on MongoDB in GeoJSON form (SSMG) and a shapefile storage method based on PostgreSQL with open location code (OLC) geocoding (SSPOG) to solve the problem of low efficiency of electronic form management. The SSMG method consists of a JSONification tier and a cloud storage tier, while the SSPOG method consists of a geocoding tier, an extension tier, and a storage tier. Using MongoDB and PostgreSQL as databases, this study achieved two different types of high-throughput and high-efficiency methods for geochemical data storage and retrieval. Xinjiang, the largest province in China, was selected as the study area in which to test the proposed methods. Using geochemical data from shapefile as a data source, several experiments were performed to improve geochemical data storage efficiency and achieve efficient retrieval. The SSMG and SSPOG methods can be applied to improve geochemical data storage using different architectures, so as to achieve management of geochemical data organization in an efficient way, through time consumed and data compression ratio (DCR), in order to better support geological big data. The purpose of this study was to find ways to build a storage method that can improve the speed of geochemical data insertion and retrieval by using excellent big data technology to help us efficiently solve problem of geochemical data preprocessing and provide support for geochemical analysis.

ACS Style

Yinyi Cheng; Kefa Zhou; Jinlin Wang; Philippe De Maeyer; Tim Van de Voorde; Jining Yan; Shichao Cui. A Comprehensive Study of Geochemical Data Storage Performance Based on Different Management Methods. Remote Sensing 2021, 13, 3208 .

AMA Style

Yinyi Cheng, Kefa Zhou, Jinlin Wang, Philippe De Maeyer, Tim Van de Voorde, Jining Yan, Shichao Cui. A Comprehensive Study of Geochemical Data Storage Performance Based on Different Management Methods. Remote Sensing. 2021; 13 (16):3208.

Chicago/Turabian Style

Yinyi Cheng; Kefa Zhou; Jinlin Wang; Philippe De Maeyer; Tim Van de Voorde; Jining Yan; Shichao Cui. 2021. "A Comprehensive Study of Geochemical Data Storage Performance Based on Different Management Methods." Remote Sensing 13, no. 16: 3208.

Journal article
Published: 09 April 2021 in Remote Sensing
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Estimating the fractional coverage of the photosynthetic vegetation (f PV) and non-photosynthetic vegetation (f NPV) is essential for assessing the growth conditions of vegetation growth in arid areas and for monitoring environmental changes and desertification. The aim of this study was to estimate the f PV, f NPV and the fractional coverage of the bare soil (f BS) in the lower reaches of Tarim River quantitatively. The study acquired field data during September 2020 for obtaining the f PV, f NPV and f BS. Firstly, six photosynthetic vegetation indices (PVIs) and six non-photosynthetic vegetation indices (NPVIs) were calculated from Sentinel-2A image data. The PVIs include normalized difference vegetation index (NDVI), ratio vegetation index (RVI), soil adjusted vegetation index (SAVI), modified soil adjusted vegetation index (MSAVI), reduced simple ratio index (RSR) and global environment monitoring index (GEMI). Meanwhile, normalized difference index (NDI), normalized difference tillage index (NDTI), normalized difference senescent vegetation index (NDSVI), soil tillage index (STI), shortwave infrared ratio (SWIR32) and dead fuel index (DFI) constitutes the NPVIs. We then established linear regression model of different PVIs and f PV, and NPVIs and f NPV, respectively. Finally, we applied the GEMI-DFI model to analyze the spatial and seasonal variation of f PV and f NPV in the study area in 2020. The results showed that the GEMI and f PV revealed the best correlation coefficient (R 2) of 0.59, while DFI and f NPV had the best correlation of R 2 = 0.45. The accuracy of f PV, f NPV and f BS based on the determined PVIs and NPVIs as calculated by GEMI-DFI model are 0.69, 0.58 and 0.43, respectively. The f PV and f NPV are consistent with the vegetation phonological development characteristics in the study area. The study concluded that the application of the GEMI-DFI model in the f PV and f NPV estimation was sufficiently significant for monitoring the spatial and seasonal variation of vegetation and its ecological functions in arid areas.

ACS Style

Zengkun Guo; Alishir Kurban; Abdimijit Ablekim; Shupu Wu; Tim Van de Voorde; Hossein Azadi; Philippe Maeyer; Edovia Dufatanye Umwali. Estimation of Photosynthetic and Non-Photosynthetic Vegetation Coverage in the Lower Reaches of Tarim River Based on Sentinel-2A Data. Remote Sensing 2021, 13, 1458 .

AMA Style

Zengkun Guo, Alishir Kurban, Abdimijit Ablekim, Shupu Wu, Tim Van de Voorde, Hossein Azadi, Philippe Maeyer, Edovia Dufatanye Umwali. Estimation of Photosynthetic and Non-Photosynthetic Vegetation Coverage in the Lower Reaches of Tarim River Based on Sentinel-2A Data. Remote Sensing. 2021; 13 (8):1458.

Chicago/Turabian Style

Zengkun Guo; Alishir Kurban; Abdimijit Ablekim; Shupu Wu; Tim Van de Voorde; Hossein Azadi; Philippe Maeyer; Edovia Dufatanye Umwali. 2021. "Estimation of Photosynthetic and Non-Photosynthetic Vegetation Coverage in the Lower Reaches of Tarim River Based on Sentinel-2A Data." Remote Sensing 13, no. 8: 1458.

Journal article
Published: 24 February 2021 in Hydrology and Earth System Sciences
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The previous comparative studies on watersheds were mostly based on the comparison of dispersive characteristics, which lacked systemicity and causality. We proposed a causal structure-based framework for basin comparison based on the Bayesian network (BN) and focus on the basin-scale water–energy–food–ecology (WEFE) nexus. We applied it to the Syr Darya River basin (SDB) and the Amu Darya River basin (ADB), of which poor water management caused the Aral Sea disaster. The causality of the nexus was effectively compared and universality of this framework was discussed. In terms of changes in the nexus, the sensitive factor for the water supplied to the Aral Sea changed from the agricultural development during the Soviet Union period to the disputes in the WEFE nexus after the disintegration. The water–energy contradiction of the SDB is more severe than that of the ADB, partly due to the higher upstream reservoir interception capacity. It further made management of the winter surplus water downstream of the SDB more controversial. Due to this, the water–food–ecology conflict between downstream countries may escalate and turn into a long-term chronic problem. Reducing water inflow to depressions and improving the planting structure prove beneficial to the Aral Sea ecology, and this effect of the SDB is more significant. The construction of reservoirs on the Panj River of the upstream ADB should be cautious to avoid an intense water–energy conflict such as the SDB's. It is also necessary to promote the water-saving drip irrigation and to strengthen the cooperation.

ACS Style

Haiyang Shi; Geping Luo; Hongwei Zheng; Chunbo Chen; Olaf Hellwich; Jie Bai; Tie Liu; Shuang Liu; Jie Xue; Peng Cai; Huili He; Friday Uchenna Ochege; Tim Van de Voorde; Philippe de Maeyer. A novel causal structure-based framework for comparing a basin-wide water–energy–food–ecology nexus applied to the data-limited Amu Darya and Syr Darya river basins. Hydrology and Earth System Sciences 2021, 25, 901 -925.

AMA Style

Haiyang Shi, Geping Luo, Hongwei Zheng, Chunbo Chen, Olaf Hellwich, Jie Bai, Tie Liu, Shuang Liu, Jie Xue, Peng Cai, Huili He, Friday Uchenna Ochege, Tim Van de Voorde, Philippe de Maeyer. A novel causal structure-based framework for comparing a basin-wide water–energy–food–ecology nexus applied to the data-limited Amu Darya and Syr Darya river basins. Hydrology and Earth System Sciences. 2021; 25 (2):901-925.

Chicago/Turabian Style

Haiyang Shi; Geping Luo; Hongwei Zheng; Chunbo Chen; Olaf Hellwich; Jie Bai; Tie Liu; Shuang Liu; Jie Xue; Peng Cai; Huili He; Friday Uchenna Ochege; Tim Van de Voorde; Philippe de Maeyer. 2021. "A novel causal structure-based framework for comparing a basin-wide water–energy–food–ecology nexus applied to the data-limited Amu Darya and Syr Darya river basins." Hydrology and Earth System Sciences 25, no. 2: 901-925.

Communication
Published: 28 January 2021 in Remote Sensing
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In this short communication, we describe the shortcomings and pitfalls of a commonly used method to detect ground materials that relies on setting thresholds for normalized difference indices. We analyze this method critically and present some experimental results on the USGS and ECOSTRESS spectral libraries and on real Sentinel-2 and Landsat-8 images. We demonstrate the risk of commission errors and provide some suggestions to reduce it.

ACS Style

Fen Chen; Tim Van de Voorde; Dar Roberts; Haojie Zhao; Jingbo Chen. Detection of Ground Materials Using Normalized Difference Indices with a Threshold: Risk and Ways to Improve. Remote Sensing 2021, 13, 450 .

AMA Style

Fen Chen, Tim Van de Voorde, Dar Roberts, Haojie Zhao, Jingbo Chen. Detection of Ground Materials Using Normalized Difference Indices with a Threshold: Risk and Ways to Improve. Remote Sensing. 2021; 13 (3):450.

Chicago/Turabian Style

Fen Chen; Tim Van de Voorde; Dar Roberts; Haojie Zhao; Jingbo Chen. 2021. "Detection of Ground Materials Using Normalized Difference Indices with a Threshold: Risk and Ways to Improve." Remote Sensing 13, no. 3: 450.

Journal article
Published: 04 January 2021 in Nature Ecology & Evolution
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Technology is transforming societies worldwide. A major innovation is the emergence of robotics and autonomous systems (RAS), which have the potential to revolutionize cities for both people and nature. Nonetheless, the opportunities and challenges associated with RAS for urban ecosystems have yet to be considered systematically. Here, we report the findings of an online horizon scan involving 170 expert participants from 35 countries. We conclude that RAS are likely to transform land use, transport systems and human–nature interactions. The prioritized opportunities were primarily centred on the deployment of RAS for the monitoring and management of biodiversity and ecosystems. Fewer challenges were prioritized. Those that were emphasized concerns surrounding waste from unrecovered RAS, and the quality and interpretation of RAS-collected data. Although the future impacts of RAS for urban ecosystems are difficult to predict, examining potentially important developments early is essential if we are to avoid detrimental consequences but fully realize the benefits. The future challenges and potential opportunities of robotics and autonomous systems in urban ecosystems, and how they may impact biodiversity, are explored and prioritized via a global horizon scan of 170 experts.

ACS Style

Mark A. Goddard; Zoe G. Davies; Solène Guenat; Mark J. Ferguson; Jessica C. Fisher; Adeniran Akanni; Teija Ahjokoski; Pippin M. L. Anderson; Fabio Angeoletto; Constantinos Antoniou; Adam J. Bates; Andrew Barkwith; Adam Berland; Christopher J. Bouch; Christine C. Rega-Brodsky; Loren B. Byrne; David Cameron; Rory Canavan; Tim Chapman; Stuart Connop; Steve Crossland; Marie C. Dade; David A. Dawson; Cynnamon Dobbs; Colleen T. Downs; Erle C. Ellis; Francisco J. Escobedo; Paul Gobster; Natalie Marie Gulsrud; Burak Guneralp; Amy K. Hahs; James D. Hale; Christopher Hassall; Marcus Hedblom; Dieter F. Hochuli; Tommi Inkinen; Ioan-Cristian Ioja; Dave Kendal; Tom Knowland; Ingo Kowarik; Simon J. Langdale; Susannah B. Lerman; Ian MacGregor-Fors; Peter Manning; Peter Massini; Stacey McLean; David D. Mkwambisi; Alessandro Ossola; Gabriel Pérez Luque; Luis Pérez-Urrestarazu; Katia Perini; Gad Perry; Tristan J. Pett; Kate E. Plummer; Raoufou A. Radji; Uri Roll; Simon G. Potts; Heather Rumble; Jon P. Sadler; Stevienna de Saille; Sebastian Sautter; Catherine E. Scott; Assaf Shwartz; Tracy Smith; Robbert P. H. Snep; Carl D. Soulsbury; Margaret C. Stanley; Tim Van de Voorde; Stephen J. Venn; Philip H. Warren; Carla-Leanne Washbourne; Mark Whitling; Nicholas S. G. Williams; Jun Yang; Kumelachew Yeshitela; Ken P. Yocom; Martin Dallimer. A global horizon scan of the future impacts of robotics and autonomous systems on urban ecosystems. Nature Ecology & Evolution 2021, 5, 219 -230.

AMA Style

Mark A. Goddard, Zoe G. Davies, Solène Guenat, Mark J. Ferguson, Jessica C. Fisher, Adeniran Akanni, Teija Ahjokoski, Pippin M. L. Anderson, Fabio Angeoletto, Constantinos Antoniou, Adam J. Bates, Andrew Barkwith, Adam Berland, Christopher J. Bouch, Christine C. Rega-Brodsky, Loren B. Byrne, David Cameron, Rory Canavan, Tim Chapman, Stuart Connop, Steve Crossland, Marie C. Dade, David A. Dawson, Cynnamon Dobbs, Colleen T. Downs, Erle C. Ellis, Francisco J. Escobedo, Paul Gobster, Natalie Marie Gulsrud, Burak Guneralp, Amy K. Hahs, James D. Hale, Christopher Hassall, Marcus Hedblom, Dieter F. Hochuli, Tommi Inkinen, Ioan-Cristian Ioja, Dave Kendal, Tom Knowland, Ingo Kowarik, Simon J. Langdale, Susannah B. Lerman, Ian MacGregor-Fors, Peter Manning, Peter Massini, Stacey McLean, David D. Mkwambisi, Alessandro Ossola, Gabriel Pérez Luque, Luis Pérez-Urrestarazu, Katia Perini, Gad Perry, Tristan J. Pett, Kate E. Plummer, Raoufou A. Radji, Uri Roll, Simon G. Potts, Heather Rumble, Jon P. Sadler, Stevienna de Saille, Sebastian Sautter, Catherine E. Scott, Assaf Shwartz, Tracy Smith, Robbert P. H. Snep, Carl D. Soulsbury, Margaret C. Stanley, Tim Van de Voorde, Stephen J. Venn, Philip H. Warren, Carla-Leanne Washbourne, Mark Whitling, Nicholas S. G. Williams, Jun Yang, Kumelachew Yeshitela, Ken P. Yocom, Martin Dallimer. A global horizon scan of the future impacts of robotics and autonomous systems on urban ecosystems. Nature Ecology & Evolution. 2021; 5 (2):219-230.

Chicago/Turabian Style

Mark A. Goddard; Zoe G. Davies; Solène Guenat; Mark J. Ferguson; Jessica C. Fisher; Adeniran Akanni; Teija Ahjokoski; Pippin M. L. Anderson; Fabio Angeoletto; Constantinos Antoniou; Adam J. Bates; Andrew Barkwith; Adam Berland; Christopher J. Bouch; Christine C. Rega-Brodsky; Loren B. Byrne; David Cameron; Rory Canavan; Tim Chapman; Stuart Connop; Steve Crossland; Marie C. Dade; David A. Dawson; Cynnamon Dobbs; Colleen T. Downs; Erle C. Ellis; Francisco J. Escobedo; Paul Gobster; Natalie Marie Gulsrud; Burak Guneralp; Amy K. Hahs; James D. Hale; Christopher Hassall; Marcus Hedblom; Dieter F. Hochuli; Tommi Inkinen; Ioan-Cristian Ioja; Dave Kendal; Tom Knowland; Ingo Kowarik; Simon J. Langdale; Susannah B. Lerman; Ian MacGregor-Fors; Peter Manning; Peter Massini; Stacey McLean; David D. Mkwambisi; Alessandro Ossola; Gabriel Pérez Luque; Luis Pérez-Urrestarazu; Katia Perini; Gad Perry; Tristan J. Pett; Kate E. Plummer; Raoufou A. Radji; Uri Roll; Simon G. Potts; Heather Rumble; Jon P. Sadler; Stevienna de Saille; Sebastian Sautter; Catherine E. Scott; Assaf Shwartz; Tracy Smith; Robbert P. H. Snep; Carl D. Soulsbury; Margaret C. Stanley; Tim Van de Voorde; Stephen J. Venn; Philip H. Warren; Carla-Leanne Washbourne; Mark Whitling; Nicholas S. G. Williams; Jun Yang; Kumelachew Yeshitela; Ken P. Yocom; Martin Dallimer. 2021. "A global horizon scan of the future impacts of robotics and autonomous systems on urban ecosystems." Nature Ecology & Evolution 5, no. 2: 219-230.

Preprint content
Published: 09 October 2020
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The previous comparative studies on watersheds were mostly based on the comparison of dispersive characteristics, which lacked systemicity and causality. We proposed a causal structure-based framework for basin comparison based on the Bayesian network (BN), and focus on the basin-scale water-energy-food-ecology (WEFE) nexuses. We applied it to the Syr Darya river basin (SDB) and the Amu Darya river basin (ADB) that caused the Aral Sea disaster. The causality of the nexuses was effectively compared and universality of this framework was discussed. In terms of changes of the nexuses, the sensitive factor for the water supplied to the Aral Sea changed from the agricultural development during the Soviet Union period to the disputes in the WEFE nexuses after the disintegration. The water-energy contradiction of SDB is more severe than that of ADB partly due to the higher upstream reservoir interception capacity. It further made management of the winter surplus water downstream of SDB more controversial. Due to this, the water-food-ecology conflict between downstream countries may escalate and turn into a long-term chronic problem. Reducing water inflow to depressions and improving the planting structure prove beneficial to the Aral Sea ecology and this effect of SDB is more significant. The construction of reservoirs on the Panj river of the upstream ADB should be cautious to avoid an intense water-energy conflict as SDB. It is also necessary to promote the water-saving drip irrigation and to strengthen the cooperation.

ACS Style

Haiyang Shi; Geping Luo; Hongwei Zheng; Chunbo Chen; Jie Bai; Tie Liu; Shuang Liu; Jie Xue; Peng Cai; Huili He; Friday Uchenna Ochege; Tim van de Voorde; Philippe de Maeyer. A novel causal structure-based framework for comparing basin-wide water-energy-food-ecology nexuses applied to the data-limited Amu Darya and Syr Darya river basins. 2020, 2020, 1 -36.

AMA Style

Haiyang Shi, Geping Luo, Hongwei Zheng, Chunbo Chen, Jie Bai, Tie Liu, Shuang Liu, Jie Xue, Peng Cai, Huili He, Friday Uchenna Ochege, Tim van de Voorde, Philippe de Maeyer. A novel causal structure-based framework for comparing basin-wide water-energy-food-ecology nexuses applied to the data-limited Amu Darya and Syr Darya river basins. . 2020; 2020 ():1-36.

Chicago/Turabian Style

Haiyang Shi; Geping Luo; Hongwei Zheng; Chunbo Chen; Jie Bai; Tie Liu; Shuang Liu; Jie Xue; Peng Cai; Huili He; Friday Uchenna Ochege; Tim van de Voorde; Philippe de Maeyer. 2020. "A novel causal structure-based framework for comparing basin-wide water-energy-food-ecology nexuses applied to the data-limited Amu Darya and Syr Darya river basins." 2020, no. : 1-36.

Journal article
Published: 24 August 2020 in The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences
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Agriculture is one of the most critical sectors of the Mongolian economy. In Mongolia, land degradation is increasing in the cropland region, especially in a cultivated area. The country has challenges to identify new croplands with sufficient capacity for cultivation, especially for local decision-makers. GIS applications tremendously help science in making land assessments. This study was carried out in Bornuur soum, Mongolia. The goal of this study to estimate that best suitable area for supporting crop production in Bornuur soum, using a GIS-based multi-criteria analysis (MCA) and remote sensing. GIS-based multi-criteria analysis (MCA) has been widely used in land suitability analyses in many countries. In this research, the GIS-based spatial MCA among the Analytical Hierarchy Process (AHP) method has employed. The approach was enhanced for each criterion which as soil, topography and vegetation. The opinions of agronomist experts and a literature review helped in identifying criteria (soil data, topography, water and vegetation data) that are necessary to determine areas suitable for crops. The detailed cropland suitability maps indicate that 46.12 % is highly suitable for cropland, 34.68 % is moderate suitable, 13.64 % is marginal suitable and 5.56 % is not suitable. The MCA and AHP tools play an essential role in the multi-criteria analysis. Therefore, the results of these methods allow us to estimate an appropriate area for cultivation in Bornuur soum, Tuv province. The crop suitability method implies significant decisions on different levels and the result will be used for cropland management plan to make a decision. It is an integral role in agricultural management and land evaluation. Future research should further develop this method by including socio-economic (potential citizens for agriculture, current crop growth, water resource, etc.) and environmental variables (rainfall, vegetation types, permafrost distribution, etc.) to obtain specific results. However, it could be also be applied for a single crop type (mainly barley, wheat and potato) in Mongolia.

ACS Style

E. Natsagdorj; T. Renchin; P. De Maeyer; R. Goossens; T. Van de Voorde; B. Darkhijav. A GIS-BASED MULTI-CRITERIA ANALYSIS ON CROPLAND SUITABILITY IN BORNUUR SOUM, MONGOLIA. The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences 2020, XLIII-B4-2, 149 -156.

AMA Style

E. Natsagdorj, T. Renchin, P. De Maeyer, R. Goossens, T. Van de Voorde, B. Darkhijav. A GIS-BASED MULTI-CRITERIA ANALYSIS ON CROPLAND SUITABILITY IN BORNUUR SOUM, MONGOLIA. The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences. 2020; XLIII-B4-2 ():149-156.

Chicago/Turabian Style

E. Natsagdorj; T. Renchin; P. De Maeyer; R. Goossens; T. Van de Voorde; B. Darkhijav. 2020. "A GIS-BASED MULTI-CRITERIA ANALYSIS ON CROPLAND SUITABILITY IN BORNUUR SOUM, MONGOLIA." The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XLIII-B4-2, no. : 149-156.

Journal article
Published: 12 March 2020 in Remote Sensing of Environment
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Commonly applied water indices such as the normalized difference water index (NDWI) and the modified normalized difference water index (MNDWI) were originally conceived for medium spatial resolution remote sensing images. In recent decades, high spatial resolution imagery has shown considerable potential for deriving accurate land cover maps of urban environments. Applying traditional water indices directly on this type of data, however, leads to severe misclassifications as there are many materials in urban areas that are confused with water. Furthermore, threshold parameters must generally be fine-tuned to obtain optimal results. In this paper, we propose a new open surface water detection method for urbanized areas. We suggest using inequality constraints as well as physical magnitude constraints to identify water from urban scenes. Our experimental results on spectral libraries and real high spatial resolution remote sensing images demonstrate that by using a set of suggested fixed threshold values, the proposed method outperforms or obtains comparable results with algorithms based on traditional water indices that need to be fine-tuned to obtain optimal results. When applied to the ASTER and ECOSTRESS spectral libraries, our method identified 3677 out of 3695 non-water spectra. By contrast, NDWI and MNDWI only identified 2934 and 2918 spectra. Results on three real hyperspectral images demonstrated that the proposed method successfully identified normal water bodies, meso-eutrophic water bodies, and most of the muddy water bodies in the scenes with F-measure values of 0.91, 0.94 and 0.82 for the three scenes. For surface glint and hyper-eutrophic water, our method was not as effective as could be expected. We observed that the commonly used threshold value of 0 for NDWI and MNDWI results in greater levels of confusion, with F-measures of 0.83, 0.64 and 0.64 (NDWI) and 0.77, 0.63 and 0.59 (MNDWI). The proposed method also achieves higher precision than the untuned NDWI and MNDWI with the same recall values. Next to numerical performance, the proposed method is also physically justified, easy-to implement, and computationally efficient, which suggests that it has potential to be applied in large scale water detection problem.

ACS Style

Fen Chen; Xingzhuang Chen; Tim Van de Voorde; Dar Roberts; Huajun Jiang; Wenbo Xu. Open water detection in urban environments using high spatial resolution remote sensing imagery. Remote Sensing of Environment 2020, 242, 111706 .

AMA Style

Fen Chen, Xingzhuang Chen, Tim Van de Voorde, Dar Roberts, Huajun Jiang, Wenbo Xu. Open water detection in urban environments using high spatial resolution remote sensing imagery. Remote Sensing of Environment. 2020; 242 ():111706.

Chicago/Turabian Style

Fen Chen; Xingzhuang Chen; Tim Van de Voorde; Dar Roberts; Huajun Jiang; Wenbo Xu. 2020. "Open water detection in urban environments using high spatial resolution remote sensing imagery." Remote Sensing of Environment 242, no. : 111706.

Journal article
Published: 31 May 2019 in Sustainability
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Water resources are increasingly under stress in Central Asia because downstream countries are highly dependent on upstream countries. Water is essential for irrigation and is becoming scarcer due to climate change and human activities. Based on 20 hydrological stations, this study firstly analyzed the annual and seasonal spatial–temporal changes of the river discharges, precipitation, and temperature in the Syr Darya River Basin and then the possible relationships between these factors were detected. Finally, the potential reasons for the river discharge variations have been discussed. The results show that the river discharges in the upper stream of the basin had significantly risen from 1930 to 2006, mainly due to the increase in temperature (approximately 0.3 °C per decade), which accelerated the melting of glaciers, while it decreased in the middle and lower regions due to the rising irrigation. In the middle of the basin, the expansion of the construction land (128.83 km2/year) and agricultural land (66.68 km2/year) from 1992 to 2015 has significantly augmented the water consumption. The operations of reservoirs and irrigation canals significantly intercepted the river discharge from the upper streams, causing a sharp decline in the river discharges in the middle and lower reaches of the Syr Darya River in 1973. The outcomes obtained from this study allowed us to understand the changes in the river discharges and provided essential information for effective water resource management in the Syr Darya River Basin.

ACS Style

Shan Zou; Abuduwaili Jilili; Weili Duan; Philippe Maeyer; Tim De Voorde. Human and Natural Impacts on the Water Resources in the Syr Darya River Basin, Central Asia. Sustainability 2019, 11, 3084 .

AMA Style

Shan Zou, Abuduwaili Jilili, Weili Duan, Philippe Maeyer, Tim De Voorde. Human and Natural Impacts on the Water Resources in the Syr Darya River Basin, Central Asia. Sustainability. 2019; 11 (11):3084.

Chicago/Turabian Style

Shan Zou; Abuduwaili Jilili; Weili Duan; Philippe Maeyer; Tim De Voorde. 2019. "Human and Natural Impacts on the Water Resources in the Syr Darya River Basin, Central Asia." Sustainability 11, no. 11: 3084.

Journal article
Published: 22 May 2018 in International Journal of Applied Earth Observation and Geoinformation
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High spatial resolution hyperspectral imagery has shown considerable potential for deriving accurate land cover maps in urban areas. In this paper, a new classification framework for mapping land cover in urban environments using high spatial resolution hyperspectral data was proposed. The proposed classification scheme was applied to map urban land cover using APEX data in the city of Baden, Switzerland. We first used the NDWI and NDVI indices to separate the land cover in the scene into three main classes: water, vegetation and non-vegetated surface. Then we partitioned the scene into many superpixels and applied classification using a SVM separately on the vegetation and non-vegetated surfaces. Soil was classified both in vegetation and non-vegetated surface, and these two soil results were merged in the final classification map. Shadows were initially classified in shaded vegetation surfaces and shaded non-vegetated surfaces, and then they were further classified into meaningful land cover categories. Our experimental results demonstrate that the proposed classification framework is well suited for mapping land cover in urban environments using high resolution hyperspectral data. Although the proposed method performs better than traditional methods in terms of soil classification accuracy, our findings emphasize that the soil class should be interpreted with caution in urban land cover maps derived from remote sensing data, even when high spatial resolution hyperspectral data are used. Results from this study also demonstrate that although shaded surfaces are generally classified as a single category in urban environments, in high resolution hyperspectral data, the shadows can be further classified into meaningful land cover classes with an acceptable accuracy.

ACS Style

Fen Chen; Huajun Jiang; Tim Van de Voorde; Sijia Lu; Wenbo Xu; Yan Zhou. Land cover mapping in urban environments using hyperspectral APEX data: A study case in Baden, Switzerland. International Journal of Applied Earth Observation and Geoinformation 2018, 71, 70 -82.

AMA Style

Fen Chen, Huajun Jiang, Tim Van de Voorde, Sijia Lu, Wenbo Xu, Yan Zhou. Land cover mapping in urban environments using hyperspectral APEX data: A study case in Baden, Switzerland. International Journal of Applied Earth Observation and Geoinformation. 2018; 71 ():70-82.

Chicago/Turabian Style

Fen Chen; Huajun Jiang; Tim Van de Voorde; Sijia Lu; Wenbo Xu; Yan Zhou. 2018. "Land cover mapping in urban environments using hyperspectral APEX data: A study case in Baden, Switzerland." International Journal of Applied Earth Observation and Geoinformation 71, no. : 70-82.

Journal article
Published: 12 March 2018 in Remote Sensing
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Fast and automatic detection of airports from remote sensing images is useful for many military and civilian applications. In this paper, a fast automatic detection method is proposed to detect airports from remote sensing images based on convolutional neural networks using the Faster R-CNN algorithm. This method first applies a convolutional neural network to generate candidate airport regions. Based on the features extracted from these proposals, it then uses another convolutional neural network to perform airport detection. By taking the typical elongated linear geometric shape of airports into consideration, some specific improvements to the method are proposed. These approaches successfully improve the quality of positive samples and achieve a better accuracy in the final detection results. Experimental results on an airport dataset, Landsat 8 images, and a Gaofen-1 satellite scene demonstrate the effectiveness and efficiency of the proposed method.

ACS Style

Fen Chen; Ruilong Ren; Tim Van De Voorde; Wenbo Xu; Guiyun Zhou; Yan Zhou. Fast Automatic Airport Detection in Remote Sensing Images Using Convolutional Neural Networks. Remote Sensing 2018, 10, 443 .

AMA Style

Fen Chen, Ruilong Ren, Tim Van De Voorde, Wenbo Xu, Guiyun Zhou, Yan Zhou. Fast Automatic Airport Detection in Remote Sensing Images Using Convolutional Neural Networks. Remote Sensing. 2018; 10 (3):443.

Chicago/Turabian Style

Fen Chen; Ruilong Ren; Tim Van De Voorde; Wenbo Xu; Guiyun Zhou; Yan Zhou. 2018. "Fast Automatic Airport Detection in Remote Sensing Images Using Convolutional Neural Networks." Remote Sensing 10, no. 3: 443.

Journal article
Published: 01 July 2017 in Remote Sensing of Environment
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ACS Style

Fen Chen; Ke Wang; Tim Van de Voorde; Ting Feng Tang. Mapping urban land cover from high spatial resolution hyperspectral data: An approach based on simultaneously unmixing similar pixels with jointly sparse spectral mixture analysis. Remote Sensing of Environment 2017, 196, 324 -342.

AMA Style

Fen Chen, Ke Wang, Tim Van de Voorde, Ting Feng Tang. Mapping urban land cover from high spatial resolution hyperspectral data: An approach based on simultaneously unmixing similar pixels with jointly sparse spectral mixture analysis. Remote Sensing of Environment. 2017; 196 ():324-342.

Chicago/Turabian Style

Fen Chen; Ke Wang; Tim Van de Voorde; Ting Feng Tang. 2017. "Mapping urban land cover from high spatial resolution hyperspectral data: An approach based on simultaneously unmixing similar pixels with jointly sparse spectral mixture analysis." Remote Sensing of Environment 196, no. : 324-342.

Journal article
Published: 16 November 2016 in International Journal of Digital Earth
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Tim Van de Voorde. Spatially explicit urban green indicators for characterizing vegetation cover and public green space proximity: a case study on Brussels, Belgium. International Journal of Digital Earth 2016, 10, 798 -813.

AMA Style

Tim Van de Voorde. Spatially explicit urban green indicators for characterizing vegetation cover and public green space proximity: a case study on Brussels, Belgium. International Journal of Digital Earth. 2016; 10 (8):798-813.

Chicago/Turabian Style

Tim Van de Voorde. 2016. "Spatially explicit urban green indicators for characterizing vegetation cover and public green space proximity: a case study on Brussels, Belgium." International Journal of Digital Earth 10, no. 8: 798-813.

Journal article
Published: 01 January 2016 in Ecological Indicators
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Land use change models are powerful tools that allow planners and policy makers to assess the long-term spatial and environmental impacts of their decisions. In order for these models to produce a realistic output, they should be properly calibrated. This is usually achieved by comparing simulated land-use maps of dates in the past to reference land-use maps of a corresponding date. As land-use data are often not readily or frequently available, we propose a two-stage calibration framework that includes existing land-use maps as well as remote sensing derived maps of the urban extent. Urban growth patterns for the Dublin area represented by remote sensing based maps were compared to simulated growth using spatial metrics in order to fine-tune the calibration of the MOLAND urban growth model of Dublin. We then used the calibrated model to forecast future urban growth according to four urban planning scenarios that have been defined for the Strategic Environmental Assessment of the Greater Dublin Area. We examined a selection of spatial metrics in order to determine their sensitivity to differences in spatial patterns between simulated and remote sensing derived data. We also investigated whether these metrics are useful to characterise future changes in the urban spatial structure that ensue from the planning scenarios. We found that with the exception of some metrics that strongly respond to differences in the amount of urban land, most metrics showed similar trends for simulated and remote sensing derived maps. Most metrics were also able to distinguish the growth patterns induced by the different spatial planning scenarios. The “business as usual scenario” in particular showed a clearly distinct trend compared to the other scenarios. We could also conclude that the urban growth pattern of Dublin as observed from both the remote sensing derived maps and the simulated maps of future land use seems to confirm the theory of alternating phases of diffusive growth and coalescence.

ACS Style

Tim Van de Voorde; Johannes van der Kwast; Lien Poelmans; Frank Canters; Marc Binard; Yves Cornet; Guy Engelen; Inge Uljee; Harutyun Shahumyan; Brendan Williams; Sheila Convery; Carlo LaValle. Projecting alternative urban growth patterns: The development and application of a remote sensing assisted calibration framework for the Greater Dublin Area. Ecological Indicators 2016, 60, 1056 -1069.

AMA Style

Tim Van de Voorde, Johannes van der Kwast, Lien Poelmans, Frank Canters, Marc Binard, Yves Cornet, Guy Engelen, Inge Uljee, Harutyun Shahumyan, Brendan Williams, Sheila Convery, Carlo LaValle. Projecting alternative urban growth patterns: The development and application of a remote sensing assisted calibration framework for the Greater Dublin Area. Ecological Indicators. 2016; 60 ():1056-1069.

Chicago/Turabian Style

Tim Van de Voorde; Johannes van der Kwast; Lien Poelmans; Frank Canters; Marc Binard; Yves Cornet; Guy Engelen; Inge Uljee; Harutyun Shahumyan; Brendan Williams; Sheila Convery; Carlo LaValle. 2016. "Projecting alternative urban growth patterns: The development and application of a remote sensing assisted calibration framework for the Greater Dublin Area." Ecological Indicators 60, no. : 1056-1069.

Journal article
Published: 01 September 2014 in International Journal of Applied Earth Observation and Geoinformation
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Kasper Cockx; Tim Van De Voorde; Frank Canters. Quantifying uncertainty in remote sensing-based urban land-use mapping. International Journal of Applied Earth Observation and Geoinformation 2014, 31, 154 -166.

AMA Style

Kasper Cockx, Tim Van De Voorde, Frank Canters. Quantifying uncertainty in remote sensing-based urban land-use mapping. International Journal of Applied Earth Observation and Geoinformation. 2014; 31 ():154-166.

Chicago/Turabian Style

Kasper Cockx; Tim Van De Voorde; Frank Canters. 2014. "Quantifying uncertainty in remote sensing-based urban land-use mapping." International Journal of Applied Earth Observation and Geoinformation 31, no. : 154-166.

Journal article
Published: 13 May 2013 in The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences
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Building urban growth models typically involves a process of historic calibration based on historic time series of land-use maps, usually obtained from satellite imagery. Both the remote sensing data analysis to infer land use and the subsequent modelling of land-use change are subject to uncertainties, which may have an impact on the accuracy of future land-use predictions. Our research aims to quantify and reduce these uncertainties by means of a particle filter data assimilation approach that incorporates uncertainty in land-use mapping and land-use model parameter assessment into the calibration process. This paper focuses on part of this work, more in particular the modelling of uncertainties associated with the impervious surface cover estimation and urban land-use classification adopted in the land-use mapping approach. Both stages are submitted to a Monte Carlo simulation to assess their relative contribution to and their combined impact on the uncertainty in the derived land-use maps. The approach was applied on the central part of the Flanders region (Belgium), using a time-series of Landsat/SPOT-HRV data covering the years 1987, 1996, 2005 and 2012. Although the most likely land-use map obtained from the simulation is very similar to the original classification, it is shown that the errors related to the impervious surface sub-pixel fraction estimation have a strong impact on the land-use map’s uncertainty. Hence, incorporating uncertainty in the land-use change model calibration through particle filter data assimilation is proposed to address the uncertainty observed in the derived land-use maps and to reduce uncertainty in future land-use predictions.

ACS Style

K. Cockx; T. Van de Voorde; F. Canters; L. Poelmans; I. Uljee; G. Engelen; Kor de Jong; Derek Karssenberg; Johannes van der Kwast. INCORPORATING LAND-USE MAPPING UNCERTAINTY IN REMOTE SENSING BASED CALIBRATION OF LAND-USE CHANGE MODELS. The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences 2013, XL-2/W1, 7 -12.

AMA Style

K. Cockx, T. Van de Voorde, F. Canters, L. Poelmans, I. Uljee, G. Engelen, Kor de Jong, Derek Karssenberg, Johannes van der Kwast. INCORPORATING LAND-USE MAPPING UNCERTAINTY IN REMOTE SENSING BASED CALIBRATION OF LAND-USE CHANGE MODELS. The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences. 2013; XL-2/W1 ():7-12.

Chicago/Turabian Style

K. Cockx; T. Van de Voorde; F. Canters; L. Poelmans; I. Uljee; G. Engelen; Kor de Jong; Derek Karssenberg; Johannes van der Kwast. 2013. "INCORPORATING LAND-USE MAPPING UNCERTAINTY IN REMOTE SENSING BASED CALIBRATION OF LAND-USE CHANGE MODELS." The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XL-2/W1, no. : 7-12.

Journal article
Published: 01 April 2013 in International Journal of Applied Earth Observation and Geoinformation
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This paper aims at developing a methodology for assessing urban dynamics in urban catchments and the related impact on hydrology. Using a multi-temporal remote sensing supported hydrological modelling approach an improved simulation of runoff for urban areas is targeted. A ime-series of five medium resolution urban masks and corresponding sub-pixel sealed surface proportions maps was generated from Landsat and SPOT imagery. The consistency of the urban mask and sealed surface proportion timeseries was imposed through an urban change trajectory analysis. The physically based rainfall-runoff model WetSpa was successfully adapted for integration of remote sensing derived information of detailed urban land use and sealed surface characteristics. A first scenario compares the original land-use class based approach for hydrological parameterisation with a remote sensing sub-pixel based approach. A second scenario assesses the impact of urban growth on hydrology. Study area is the Tolka River basin in Dublin, Ireland. The grid-based approach of WetSpa enables an optimal use of the spatially distributed properties of remote sensing derived input. Though change trajectory analysis remains little used in urban studies it is shown to be of utmost importance in case of time series analysis. The analysis enabled to assign a rational trajectory to 99% of all pixels. The study showed that consistent remote sensing derived land-use maps are preferred over alternative sources (such as CORINE) to avoid over-estimation errors, interpretation inconsistencies and assure enough spatial detail for urban studies. Scenario 1 reveals that both the class and remote sensing sub-pixel based approaches are able to simulate discharges at the catchment outlet in an equally atisfactory way, but the sub-pixel approach yields considerably higher peak discharges. The result confirms the importance of detailed information on the sealed surface proportion for hydrological simulations in urbanised catchments. In addition a major advantage with respect to hydrological parameterisation using remote sensing is the fact that it is site- and period-specific. Regarding the assessment of the impact of urbanisation (scenario 2) the hydrological simulations revealed that the steady urban growth in the Tolka basin between 1988 and 2006 had a considerable impact on peak discharges. Additionally, the hydrological response is quicker as a result of urbanisation. Spatially distributed surface runoff maps identify the zones with high runoff production. It is evident that this type of information is important for urban water management and decision makers. The results of the remote sensing supported modelling approach do not only indicate increased volumes due to urbanisation, but also identifies the locations where the most relevant impacts took place.status: publishe

ACS Style

B. Verbeiren; T. Van De Voorde; F. Canters; M. Binard; Y. Cornet; O. Batelaan. Assessing urbanisation effects on rainfall-runoff using a remote sensing supported modelling strategy. International Journal of Applied Earth Observation and Geoinformation 2013, 21, 92 -102.

AMA Style

B. Verbeiren, T. Van De Voorde, F. Canters, M. Binard, Y. Cornet, O. Batelaan. Assessing urbanisation effects on rainfall-runoff using a remote sensing supported modelling strategy. International Journal of Applied Earth Observation and Geoinformation. 2013; 21 ():92-102.

Chicago/Turabian Style

B. Verbeiren; T. Van De Voorde; F. Canters; M. Binard; Y. Cornet; O. Batelaan. 2013. "Assessing urbanisation effects on rainfall-runoff using a remote sensing supported modelling strategy." International Journal of Applied Earth Observation and Geoinformation 21, no. : 92-102.

Conference paper
Published: 01 April 2013 in Joint Urban Remote Sensing Event 2013
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Images from medium-resolution satellites are frequently used to study changes in urban vegetation or impervious surface cover over relatively long time periods. In this paper, we applied both “hard” and “soft” mapping methods on two images covering the Brussels Capital Region in a time span of roughly 20 years. Although soft approaches are more accurate because they take the occurrence of mixed pixels into account, errors that result from the application of sub-pixel proportion estimation methods nevertheless propagate if the maps are used for change analysis. In this paper, we propose a method to take uncertainty in sub-pixel classification into account when producing change maps.

ACS Style

Tim Van De Voorde; Frank Canters. Mapping the uncertainty of changes in vegetation cover in and around the brussels capital region. Joint Urban Remote Sensing Event 2013 2013, 123 -126.

AMA Style

Tim Van De Voorde, Frank Canters. Mapping the uncertainty of changes in vegetation cover in and around the brussels capital region. Joint Urban Remote Sensing Event 2013. 2013; ():123-126.

Chicago/Turabian Style

Tim Van De Voorde; Frank Canters. 2013. "Mapping the uncertainty of changes in vegetation cover in and around the brussels capital region." Joint Urban Remote Sensing Event 2013 , no. : 123-126.

Journal article
Published: 01 October 2012 in International Journal of Applied Earth Observation and Geoinformation
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Wiesam Essa; Boud Verbeiren; Johannes van der Kwast; Tim Van de Voorde; Okke Batelaan. Evaluation of the DisTrad thermal sharpening methodology for urban areas. International Journal of Applied Earth Observation and Geoinformation 2012, 19, 163 -172.

AMA Style

Wiesam Essa, Boud Verbeiren, Johannes van der Kwast, Tim Van de Voorde, Okke Batelaan. Evaluation of the DisTrad thermal sharpening methodology for urban areas. International Journal of Applied Earth Observation and Geoinformation. 2012; 19 ():163-172.

Chicago/Turabian Style

Wiesam Essa; Boud Verbeiren; Johannes van der Kwast; Tim Van de Voorde; Okke Batelaan. 2012. "Evaluation of the DisTrad thermal sharpening methodology for urban areas." International Journal of Applied Earth Observation and Geoinformation 19, no. : 163-172.

Journal article
Published: 01 July 2012 in International Journal of Agricultural and Environmental Information Systems
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Land-use change models are useful tools for assessing and comparing the environmental impact of alternative policy scenarios. Their increasing popularity as spatial planning instruments also poses new scientific challenges, such as correctly calibrating the model. The challenge in model calibration is twofold: obtaining a reliable and consistent time series of land-use information and finding suitable measures to compare model output to reality. Both of these issues are addressed in this paper. The authors propose a model calibration framework that is supported by information on urban form and function derived from medium-resolution remote sensing data through newly developed spatial metrics. The remote sensing derived maps are compared to model output of the same date for two model scenarios using well-known spatial metrics. Results demonstrate a good resemblance between the simulation output and the remote sensing derived maps.

ACS Style

Tim Van De Voorde; Johannes van der Kwast; Frank Canters; Guy Engelen; Marc Binard; Yves Cornet; Inge Uljee. A Remote Sensing Based Calibration Framework for the MOLAND Urban Growth Model of Dublin. International Journal of Agricultural and Environmental Information Systems 2012, 3, 1 -21.

AMA Style

Tim Van De Voorde, Johannes van der Kwast, Frank Canters, Guy Engelen, Marc Binard, Yves Cornet, Inge Uljee. A Remote Sensing Based Calibration Framework for the MOLAND Urban Growth Model of Dublin. International Journal of Agricultural and Environmental Information Systems. 2012; 3 (2):1-21.

Chicago/Turabian Style

Tim Van De Voorde; Johannes van der Kwast; Frank Canters; Guy Engelen; Marc Binard; Yves Cornet; Inge Uljee. 2012. "A Remote Sensing Based Calibration Framework for the MOLAND Urban Growth Model of Dublin." International Journal of Agricultural and Environmental Information Systems 3, no. 2: 1-21.