5,990
Views
48
CrossRef citations to date
0
Altmetric
Articles

A workflow for Sustainable Development Goals indicators assessment based on high-resolution satellite data

ORCID Icon, ORCID Icon, ORCID Icon, ORCID Icon, &
Pages 309-321 | Received 17 Jul 2018, Accepted 14 Apr 2019, Published online: 02 May 2019

References

  • Aitsi-Selmi, A., S. Egawa, H. Sasaki, C. Wannous, and V. Murray. 2015. “The Sendai Framework for Disaster Risk Reduction: Renewing the Global Commitment to People’s Resilience, Health, and Well-being.” International Journal of Disaster Risk Science 6 (2): 164–176. doi: 10.1007/s13753-015-0050-9
  • Bandaru, V., T. O. West, D. M. Ricciuto, and R. C. Izaurralde. 2013. “Estimating Crop Net Primary Production Using National Inventory Data and MODIS-derived Parameters.” ISPRS Journal of Photogrammetry and Remote Sensing 80: 61–71. doi: 10.1016/j.isprsjprs.2013.03.005
  • Biggs, E. M., E. Bruce, B. Boruff, J. M. A. Duncan, J. Horsley, N. Pauli, K. McNeill, et al. 2015. “Sustainable Development and the Water–Energy–Food Nexus: A Perspective on Livelihoods.” Environmental Science & Policy 54: 389–397. doi: 10.1016/j.envsci.2015.08.002
  • Claverie, M., J. Ju, J. G. Masek, J. L. Dungan, E. F. Vermote, J.-C. Roger, S. Skakun, and C. O. Justice. 2018. “The Harmonized Landsat and Sentinel-2 Surface Reflectance Data Set.” Remote Sensing of Environment 219: 145–161. doi: 10.1016/j.rse.2018.09.002
  • Cowie, A. L., B. J. Orr, V. M. C. Sanchez, P. Chasek, N. D. Crossman, A. Erlewein, G. Louwagie, et al. 2018. “Land in Balance: The Scientific Conceptual Framework for Land Degradation Neutrality.” Environmental Science & Policy 79: 25–35. doi: 10.1016/j.envsci.2017.10.011
  • De Beurs, K. M., and G. M. Henebry. 2004. “Land Surface Phenology, Climatic Variation, and Institutional Change: Analyzing Agricultural Land Cover Change in Kazakhstan.” Remote Sensing of Environment 89 (4): 497–509. doi: 10.1016/j.rse.2003.11.006
  • Fileccia, T., M. Guadagni, V. Hovhera, and M. Bernoux. 2014. “Ukraine: Soil Fertility to Strengthen Climate Resilience.” Food and Agriculture Organization of the United Nations, Rome, Italy. http://www.fao.org/3/a-i3905e.pdf.
  • Franch, B., E. F. Vermote, I. Becker-Reshef, M. Claverie, J. Huang, J. Zhang, C. Justice, and J. A. Sobrino. 2015. “Improving the Timeliness of Winter Wheat Production Forecast in the United States of America, Ukraine and China Using MODIS Data and NCAR Growing Degree Day Information.” Remote Sensing of Environment 161: 131–148. doi: 10.1016/j.rse.2015.02.014
  • Ghazaryan, G., O. Dubovyk, F. Löw, M. Lavreniuk, A. Kolotii, J. Schellberg, and N. Kussul. 2018. “A Rule-based Approach for Crop Identification Using Multi-temporal and Multi-sensor Phenological Metrics.” European Journal of Remote Sensing 51 (1): 511–524. doi: 10.1080/22797254.2018.1455540
  • Gitelson, A. A., 2011. “Remote Sensing Estimation of Crop Biophysical Characteristics at Various Scales.” In Hyperspectral Remote Sensing of Vegetation, edited by Prasad S. Thenkabail, John G. Lyon, Alfredo Huete, 329–358. Boca Raton, FL: CRC Press.
  • Giuliani, G., P. Lacroix, Y. Guigoz, R. Roncella, L. Bigagli, M. Santoro, and A. Lehmann. 2017. “Bringing GEOSS Services into Practice: A Capacity Building Resource on Spatial Data Infrastructures (SDI).” Transactions in GIS 21 (4): 811–824. doi: 10.1111/tgis.12209
  • He, M., J. S. Kimball, M. P. Maneta, B. D. Maxwell, A. Moreno, S. Beguería, and X. Wu. 2018. “Regional Crop Gross Primary Productivity and Yield Estimation Using Fused Landsat-MODIS Data.” Remote Sensing 10 (3), art. num. 372.
  • Ivits, E., and M. Cherlet. 2013. “Land-productivity Dynamics Towards Integrated Assessment of Land Degradation at Global Scales.” Joint Research Centre (European Commission). European Union, doi:10.2788/59315.
  • Kingma, D. P., and J. Ba. 2014. “Adam: A Method for Stochastic Optimization.” arXiv preprint arXiv:1412.6980.
  • Kogan, F., N. Kussul, T. Adamenko, S. Skakun, O. Kravchenko, O. Kryvobok, A. Shelestov, A. Kolotii, O. Kussul, and A. Lavrenyuk. 2013. “Winter Wheat Yield Forecasting in Ukraine Based on Earth Observation, Meteorological Data and Biophysical Models.” International Journal of Applied Earth Observation and Geoinformation 23: 192–203. doi: 10.1016/j.jag.2013.01.002
  • Kussul, N., A. Kolotii, A. Shelestov, B. Yailymov, and M. Lavreniuk. 2017a. “Land Degradation Estimation from Global and National Satellite based Datasets within UN Program.” In 9th IEEE International Conference on Intelligent Data Acquisition and Advanced Computing Systems: Technology and Applications (IDAACS) (Vol. 1, pp. 383–386).
  • Kussul, N., M. Lavreniuk, A. Shelestov, and S. Skakun. 2018. “Crop Inventory at Regional Scale in Ukraine: Developing in Season and End of Season Crop Maps with Multi-temporal Optical and SAR Satellite Imagery.” European Journal of Remote Sensing 51 (1): 627–636. doi: 10.1080/22797254.2018.1454265
  • Kussul, N., M. Lavreniuk, S. Skakun, and A. Shelestov. 2017b. “Deep Learning Classification of Land Cover and Crop Types Using Remote Sensing Data.” IEEE Geoscience and Remote Sensing Letters 14 (5): 778–782. doi: 10.1109/LGRS.2017.2681128
  • Kussul, N., G. Lemoine, F. J. Gallego, S. Skakun, M. Lavreniuk, and A. Shelestov. 2016. “Parcel-based Crop Classification in Ukraine Using Landsat-8 Data and Sentinel-1A Data.” IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing 9 (6): 2500–2508. doi: 10.1109/JSTARS.2016.2560141
  • Kussul, N., S. Skakun, A. Shelestov, O. Kravchenko, F. J. Gallego, and O. Kussul. 2012. “Crop Area Estimation in Ukraine Using Satellite Data within the MARS Project.” 2012 IEEE International Geoscience and Remote Sensing Symposium: 3756–3759.
  • Kussul, N., S. Skakun, A. Shelestov, and O. Kussul. 2014. “The Use of Satellite SAR Imagery to Crop Classification in Ukraine within JECAM Project.” 2014 IEEE Geoscience and Remote Sensing Symposium: 1497–1500.
  • Lehmann, A., S. Nativi, P. Mazzetti, J. Maso, I. Serral, D. Spengler, A. Niamir, et al. 2019. “GEOEssential – Mainstreaming Workflows from Data Sources to Environment Policy Indicators with Essential Variables.” International Journal of Digital Earth. doi:10.1080/17538947.2019.1585977.
  • Lesiv, M., D. Schepaschenko, E. Moltchanova, R. Bun, M. Dürauer, A. V. Prishchepov, and N. Kussul. 2018. “Spatial Distribution of Arable and Abandoned Land Across Former Soviet Union Countries.” Scientific Data 5, art num. 180056. doi: 10.1038/sdata.2018.56
  • Li, J., and D. P. Roy. 2017. “A Global Analysis of Sentinel-2A, Sentinel-2B and Landsat-8 Data Revisit Intervals and Implications for Terrestrial Monitoring.” Remote Sensing 9 (9), art. num. 902. doi: 10.3390/rs9090903
  • López-Lozano, R., G. Duveiller, L. Seguini, M. Meroni, S. García-Condado, J. Hooker, and B. Baruth. 2015. “Towards Regional Grain Yield Forecasting with 1 km-resolution EO Biophysical Products: Strengths and Limitations at Pan-European Level.” Agricultural and Forest Meteorology 206: 12–32. doi: 10.1016/j.agrformet.2015.02.021
  • McCallum, I., S. Fritz, N. Kussul, A. Lehmann, J. Maso, C. Montzka, I. Serral, and D. Spengler. 2019. “Addressing the Food Water Energy Nexus with Earth Observation.” International Journal of Digital Earth.
  • Molod, A., L. Takacs, M. Suarez, and J. Bacmeister. 2015. “Development of the GEOS-5 Atmospheric General Circulation Model: Evolution from MERRA to MERRA2.” Geoscientific Model Development 8 (5): 1339–1356. doi: 10.5194/gmd-8-1339-2015
  • Monteith, J. L. 1972. “Solar Radiation and Productivity in Tropical Ecosystems.” The Journal of Applied Ecology 9 (3): 747–766. doi: 10.2307/2401901
  • Nativi, S., P. Mazzetti, M. Craglia, and N. Pirrone. 2014. “The GEOSS Solution for Enabling Data Interoperability and Integrative Research.” Environmental Science and Pollution Research 21 (6): 4177–4192. doi: 10.1007/s11356-013-2264-y
  • Nativi, S., P. Mazzetti, M. Santoro, F. Papeschi, M. Craglia, and O. Ochiai. 2015. “Big Data Challenges in Building the Global Earth Observation System of Systems.” Environmental Modelling & Software 68: 1–26. doi: 10.1016/j.envsoft.2015.01.017
  • Prince, S. D., and S. N. Goward. 1995. “Global Primary Production: A Remote Sensing Approach.” Journal of Biogeography 22 (4–5): 815–835. doi: 10.2307/2845983
  • Prince, S. D., J. Haskett, M. Steininger, H. Strand, and R. Wright. 2001. “Net Primary Production of US Midwest Croplands from Agricultural Harvest Yield Data.” Ecological Applications 11 (4): 1194–1205. doi: 10.1890/1051-0761(2001)011[1194:NPPOUS]2.0.CO;2
  • Shelestov, A., A. Kolotii, S. Skakun, B. Baruth, R. Lopez Lozano, and B. Yailymov. 2017a. “Biophysical Parameters Mapping Within the SPOT-5 Take 5 Initiative.” European Journal of Remote Sensing 50 (1): 300–309. doi: 10.1080/22797254.2017.1324743
  • Shelestov, A., M. Lavreniuk, N. Kussul, A. Novikov, and S. Skakun. 2017b. “Exploring Google Earth Engine Platform for Big Data Processing: Classification of Multi-temporal Satellite Imagery for Crop Mapping.” Frontiers in Earth Science 5: 17. doi: 10.3389/feart.2017.00017
  • Skakun, S., N. Kussul, A. Shelestov, and O. Kussul. 2015. “The Use of Satellite Data for Agriculture Drought Risk Quantification in Ukraine.” Geomatics, Natural Hazards and Risk 7 (3): 901–917. doi: 10.1080/19475705.2015.1016555
  • Skakun, S., N. Kussul, A. Shelestov, M. Lavreniuk, and O. Kussul. 2016. “Efficiency Assessment of Multitemporal C-Band Radarsat-2 Intensity and Landsat-8 Surface Reflectance Satellite Imagery for Crop Classification in Ukraine.” IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing 9 (8): 3712–3719. doi: 10.1109/JSTARS.2015.2454297
  • Skakun, S., E. Vermote, J.-C. Roger, and B. Franch. 2017. “Combined Use of Landsat-8 and Sentinel-2A Images for Winter Crop Mapping and Winter Wheat Yield Assessment at Regional Scale.” AIMS Geosciences 3 (2): 163–186. doi: 10.3934/geosci.2017.2.163
  • Waldner, F., D. De Abelleyra, S. R. Verón, M. Zhang, B. Wu, D. Plotnikov, S. Bartalev, et al. 2016. “Towards a Set of Agrosystem-specific Cropland Mapping Methods to Address the Global Cropland Diversity.” International Journal of Remote Sensing 37 (14): 3196–3231. doi: 10.1080/01431161.2016.1194545
  • Xin, Q., M. Broich, A. E. Suyker, L. Yu, and P. Gong. 2015. “Multi-scale Evaluation of Light use Efficiency in MODIS Gross Primary Productivity for Croplands in the Midwestern United States.” Agricultural and Forest Meteorology 201: 111–119. doi: 10.1016/j.agrformet.2014.11.004