References
- Abatzoglou, J. T., S. Z. Dobrowski, S. A. Parks, and K. C. Hegewisch. 2018. “TerraClimate, a High-resolution Global Dataset of Monthly Climate and Climatic Water Balance from 1958–2015.” Scientific Data 5 (1): 1–12. doi:https://doi.org/10.1038/sdata.2017.191.
- Alexandridis, T. K., G. Ovakoglou, I. Cherif, M. Gómez Giménez, G. Laneve, D. Kasampalis, D. Moshou, S. Kartsios, M. C. Karypidou, and E. Katragkou. 2020. “Designing AfriCultuReS Services to Support Food Security in Africa.” Transactions in GIS 25(2): 692–720.
- Bajwa, S. G., A. R. Mishra, and R. J. Norman. 2010. “Canopy Reflectance Response to Plant Nitrogen Accumulation in Rice.” Precision Agriculture 11 (5): 488–506. doi:https://doi.org/10.1007/s11119-009-9142-0.
- Baldasano, J. M. 2020. “COVID-19 Lockdown Effects on Air Quality by NO2 in the Cities of Barcelona and Madrid (Spain).” Science of the Total Environment 741: 140353. doi:https://doi.org/10.1016/j.scitotenv.2020.140353.
- Barnard, R. O., and C. C. Du Preez. 2004. “Soil Fertility in South Africa: The Last Twenty Five Years.” South African Journal of Plant and Soil 21 (5): 301–315. doi:https://doi.org/10.1080/02571862.2004.10635066.
- Battude, M., A. A. Bitar, D. Morin, J. Cros, M. Huc, C. M. Sicre, L. D. Valérie, and V. Demarez. 2016. “Estimating Maize Biomass and Yield over Large Areas Using High Spatial and Temporal Resolution Sentinel-2 like Remote Sensing Data.” Remote Sensing of Environment 184: 668–681. doi:https://doi.org/10.1016/j.rse.2016.07.030.
- Chen, Q.-X., C.-L. Huang, Y. Yuan, and H.-P. Tan. 2020. “Influence of COVID-19 Event on Air Quality and Their Association in Mainland China.” Aerosol and Air Quality Research 20: 1541–1551. doi:https://doi.org/10.4209/aaqr.2020.05.0224.
- Chen, Y., and D. Gillieson. 2009. “Evaluation of Landsat TM Vegetation Indices for Estimating Vegetation Cover on Semi-arid Rangelands: A Case Study from Australia.” Canadian Journal of Remote Sensing 35 (5): 435–446. doi:https://doi.org/10.5589/m09-037.
- Drusch, M, U Del Bello, S Carlier, O Colin, V Fernandez, F Gascon, B Hoersch, C Isola, P Laberinti, and P Martimort. 2012. “Sentinel-2: ESA’s optical high-resolution mission for GMES operational services.” Remote Sensing of Environment 120:25–36. https://doi.org/10.1016/j.rse.2011.11.026
- Gorelick, N., M. Hancher, M. Dixon, S. Ilyushchenko, D. Thau, and R. Moore. 2017. “Google Earth Engine: Planetary-scale Geospatial Analysis for Everyone.” Remote Sensing of Environment 202: 18–27. doi:https://doi.org/10.1016/j.rse.2017.06.031.
- Haboudane, D., N. Tremblay, J. R. Miller, and P. Vigneault. 2008. “Remote Estimation of Crop Chlorophyll Content Using Spectral Indices Derived from Hyperspectral Data.” Geoscience and Remote Sensing, IEEE Transactions On 46 (2): 423–437. doi:https://doi.org/10.1109/TGRS.2007.904836.
- Huntington, J. L., K. C. Hegewisch, B. Daudert, C. G. Morton, J. T. Abatzoglou, J. M. Daniel, and T. Erickson. 2017. “Climate Engine: Cloud Computing and Visualization of Climate and Remote Sensing Data for Advanced Natural Resource Monitoring and Process Understanding.” Bulletin of the American Meteorological Society 98 (11): 2397–2410. doi:https://doi.org/10.1175/BAMS-D-15-00324.1.
- Kganyago, M., P. Mhangara, T. Alexandridis, G. Laneve, G. Ovakoglou, and N. Mashiyi. 2020a. “Validation of Sentinel-2 Leaf Area Index (LAI) Product Derived from SNAP Toolbox and Its Comparison with Global LAI Products in an African Semi-arid Agricultural Landscape.” Remote Sensing Letters 11 (10): 883–892. doi:https://doi.org/10.1080/2150704X.2020.1767823.
- Kganyago, M., G. Ovakoglou, P. Mhangara, T. Alexandridis, J. Odindi, C. Adjorlolo, and M. Nosiseko 2020b. “Validation of Atmospheric Correction Approaches for Sentinel-2 under Partly-cloudy Conditions in an African Agricultural Landscape.” Paper presented at the Remote Sensing of Clouds and the Atmosphere XXV, SPIE Remote Sensing, 21-25 September 2020, Online Only, United Kingdom.
- Kganyago, M., and L. Shikwambana. 2020. “Did COVID-19 Lockdown Restrictions Have an Impact on Biomass Burning Emissions in Sub-Saharan Africa?” Aerosol and Air Quality Research 20 21(4), 200470.
- Kumar, L., and O. Mutanga. 2018. “Google Earth Engine Applications since Inception: Usage, Trends, and Potential.” Remote Sensing 10 (10): 1509. doi:https://doi.org/10.3390/rs10101509.
- Lee, Y.-J., C.-M. Yang, K.-W. Chang, and Y. Shen. 2008. “A Simple Spectral Index Using Reflectance of 735 Nm to Assess Nitrogen Status of Rice Canopy.” Agronomy Journal 100 (1): 205–212. doi:https://doi.org/10.2134/agronj2007.0018.
- Löw, F., U. Michel, S. Dech, and C. Conrad. 2013. “Impact of Feature Selection on the Accuracy and Spatial Uncertainty of Per-field Crop Classification Using Support Vector Machines.” ISPRS Journal of Photogrammetry and Remote Sensing 85: 102–119. doi:https://doi.org/10.1016/j.isprsjprs.2013.08.007.
- Massey, R., T. T. Sankey, R. G. Congalton, K. Yadav, P. S. Thenkabail, M. Ozdogan, and A. J. S. Meador. 2017. “MODIS Phenology-derived, Multi-year Distribution of Conterminous US Crop Types.” Remote Sensing of Environment 198: 490–503. doi:https://doi.org/10.1016/j.rse.2017.06.033.
- Menut, L., B. Bessagnet, G. Siour, S. Mailler, R. Pennel, and A. Cholakian. 2020. “Impact of Lockdown Measures to Combat Covid-19 on Air Quality over Western Europe.” Science of the Total Environment 741: 140426. doi:https://doi.org/10.1016/j.scitotenv.2020.140426.
- Ramoelo, A., M. A. Cho, R. Mathieu, S. Madonsela, V. D. K. Ruben, Z. Kaszta, and E. Wolff. 2015. “Monitoring Grass Nutrients and Biomass as Indicators of Rangeland Quality and Quantity Using Random Forest Modelling and WorldView-2 Data.” International Journal of Applied Earth Observation and Geoinformation 43: 43–54. doi:https://doi.org/10.1016/j.jag.2014.12.010.
- Rouse Jr, J. W. 1973. Monitoring the Vernal Advancement and Retrogradation (Green Wave Effect) of Natural Vegetation,Texas A & M University, Remote Sensing Center, NASA Earth Resources Survey Program, Washington, D.C.
- Shen, M., J. Chen, X. Zhu, and Y. Tang. 2009. “Yellow Flowers Can Decrease NDVI and EVI Values: Evidence from a Field Experiment in an Alpine Meadow.” Canadian Journal of Remote Sensing 35 (2): 99–106. doi:https://doi.org/10.5589/m09-003.
- Siche, R. 2020. “What Is the Impact of COVID-19 Disease on Agriculture?” Scientia Agropecuaria 11 (1): 3–6. doi:https://doi.org/10.17268/sci.agropecu.2020.01.00.
- Teluguntla, P., P. S. Thenkabail, A. Oliphant, J. Xiong, M. K. Gumma, R. G. Congalton, K. Yadav, and A. Huete. 2018. “A 30-m Landsat-derived Cropland Extent Product of Australia and China Using Random Forest Machine Learning Algorithm on Google Earth Engine Cloud Computing Platform.” ISPRS Journal of Photogrammetry and Remote Sensing 144: 325–340. doi:https://doi.org/10.1016/j.isprsjprs.2018.07.017.
- Tillack, A., A. Clasen, B. Kleinschmit, and F. Michael. 2014. “Estimation of the Seasonal Leaf Area Index in an Alluvial Forest Using High-resolution Satellite-based Vegetation Indices.” Remote Sensing of Environment 141: 52–63. doi:https://doi.org/10.1016/j.rse.2013.10.018.
- Wang, Y., D. Peng, L. Y. Yaqiong, J. Y. Zhang, L. Zhou, S. Zheng, F. Wang, and L. Cunjun. 2020. “Monitoring Crop Growth during the Period of the Rapid Spread of COVID-19 in China by Remote Sensing.” IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing 13: 6195–6205. doi:https://doi.org/10.1109/JSTARS.2020.3029434.
- Wu, B., R. Gommes, M. Zhang, H. Zeng, N. Yan, W. Zou, Y. Zheng, N. Zhang, S. Chang, and Q. Xing. 2015. “Global Crop Monitoring: A Satellite-based Hierarchical Approach.” Remote Sensing 7 (4): 3907–3933. doi:https://doi.org/10.3390/rs70403907.
- Xiong, J., P. Thenkabail, J. Tilton, M. Gumma, P. Teluguntla, A. Oliphant, R. Congalton, K. Yadav, and N. Gorelick. 2017. “Nominal 30-m Cropland Extent Map of Continental Africa by Integrating Pixel-based and Object-based Algorithms Using Sentinel-2 and Landsat-8 Data on Google Earth Engine.” Remote Sensing 9 (10): 1065. doi:https://doi.org/10.3390/rs9101065.
- Zhou, J., L. R. Khot, R. A. Boydston, P. N. Miklas, and L. Porter. 2018. “Low Altitude Remote Sensing Technologies for Crop Stress Monitoring: A Case Study on Spatial and Temporal Monitoring of Irrigated Pinto Bean.” Precision Agriculture 19 (3): 555–569. doi:https://doi.org/10.1007/s11119-017-9539-0.