171
Views
2
CrossRef citations to date
0
Altmetric
SI: Recent Advances in Quantitative Remote Sensing VI

Assessing 100 biophysical indices performances in the Mediterranean basin using multi-satellite data

, ORCID Icon, , &
Received 13 Dec 2022, Accepted 19 Apr 2023, Published online: 18 May 2023

References

  • Aldakheel, Y. J., A. M. Elprince, and A. I. Al-Hosaini. 2005. “Mapping of Salt-Affected Soils of Irrigated Lands in Arid Regions Using Remote Sensing and GIS.” Proceedings of 2nd International Conference on Recent Advances in Space Technologies, 467–472. 10.1109/RAST.2005.1512614.
  • Apan, A. A., A. Held, S. Phinn, and J. Markley. 2004. “Detecting Sugarcane ‘Orange Rust’ Disease Using EO-1 Hyperion Hyperspectral Imagery.” International Journal of Remote Sensing 25 (2): 489–498. doi:10.1080/01431160310001618031.
  • Bannari, A., H. Asalhi, and P. M. Teillet. 2002. “Transformed Difference Vegetation Index (TDVI) for Vegetation Cover Mapping.” IEEE International Geoscience and Remote Sensing Symposium, 5, vol.5. 3053–3055. doi:10.1109/IGARSS.2002.1026867.
  • Bannari, A., D. Morin, F. Bonn, and A. R. Huete. 1995. “A Review of Vegetation Indices.” Remote Sensing Reviews 13 (1–2): 95–120. doi:10.1080/02757259509532298.
  • Baret, F., and G. Guyot. 1991. “Potentials and Limits of Vegetation Indices of LAI and APAR Assessment.” Remote Sensing of Environment 35: 161–173. doi:10.1016/0034-4257(91)90009-U.
  • Barnes, E., T. R. Clarke, S. E. Richards, P. Colaizzi, J. Haberland, M. Kostrzewski, P. Waller, C. Choi, E. Riley, and T. L. Thompson. 2000. “Coincident Detection of Crop Water Stress, Nitrogen Status, and Canopy Density Using Ground Based Multispectral Data.” Proceedings of the 5th International Conference on Precision Agriculture, Bloomington, Minnesota 1–15.
  • Batista, J. E., N. M. Rodrigues, A. I. R. Cabral, M. J. P. Vasconcelos, A. Venturieri, L. G. T. Silva, and S. Silva. 2022. “Optical Time Series for the Separation of Land Cover Types with Similar Spectral Signatures: Cocoa Agroforest and Forest.” International Journal of Remote Sensing 43 (9): 3298–3319. doi:10.1080/01431161.2022.2089540.
  • Beck, H. E., N. E. Zimmermann, T. R. McVicar, N. Vergopolan, A. Berg, and E. F. Wood. 2018. “Present and Future Köppen-Geiger Climate Classification Maps at 1-Km Resolution.” Scientific Data 5 (1): 180214. doi:10.1038/sdata.2018.214.
  • Ben Achhab, N., N. Raissouni, A. Azyat, A. Chahboun, and M. Lahraoua. 2010. “High Performance Computing Software Package for Multitemporal Remote-Sensing Computations.” International Journal of Engineering & Technology 2: 360–365.
  • Ben Achhab, N., N. Raissouni, J. A. Sobrino, A. Chahboun, A. Azyat, M. Lahraoua, and S. El Adib. 2018. “A High Performance GPU Implementation for Multitemporal Analysis of Huge Satellite Remote Sensing Databases.” In Fifth Recent Advances in Quantitative Remote Sensing. Vol. 356. Valencia: Universitat de València.
  • Bolle, H. J., M. Eckardt, D. Koslowsky, F. Maselli, J. Melia Miralles, M. Menenti, F. S. Olesen, and S. Ljiljana Petkov, eds. 2006. Ichtiaque RasoolIchtiaque Rasool. 2006th ed. Berlin; New York: Springer.
  • Broge, N. H., and E. Leblanc. 2001. “Comparing Prediction Power and Stability of Broadband and Hyperspectral Vegetation Indices for Estimation of Green Leaf Area Index and Canopy Chlorophyll Density.” Remote Sensing of Environment 76 (2): 156–172. doi:10.1016/S0034-4257(00)00197-8.
  • Buschmann, C., and E. Nagel. 1993. “In vivo Spectroscopy and Internal Optics of Leaves as Basis for Remote Sensing of Vegetation.” International Journal of Remote Sensing 14 (4): 711–722. doi:10.1080/01431169308904370.
  • Caasi, O., C. Hongo, S. Wiyono, Y. Giamerti, D. Saito, K. Homma, and M. Shishido. 2020. “The Potential of Using Sentinel-2 Satellite Imagery in Assessing Bacterial Leaf Blight on Rice in West Java, Indonesia.” Journal of the International Society for Southeast Asian Agricultural Sciences 26 (1): 1–16.
  • Cao, Q., Y. Miao, J. Shen, W. Yu, F. Yuan, S. Cheng, S. Huang, H. Wang, W. Yang, and F. Liu. 2015. “Improving In-Season Estimation of Rice Yield Potential and Responsiveness to Topdressing Nitrogen Application with Crop Circle Active Crop Canopy Sensor.” Precision Agriculture 17: 136–154. doi:10.1007/s11119-015-9412-y.
  • Ceccato, P., N. Gobron, S. Flasse, B. Pinty, and S. Tarantola. 2002. “Designing a Spectral Index to Estimate Vegetation Water Content from Remote Sensing Data: Part 1: Theoretical Approach.” Remote Sensing of Environment 82 (2): 188–197. doi:10.1016/S0034-4257(02)00037-8.
  • Chamard, P., M. F. Courel, M. Ducousso, M. C. Guénégou, J. Le Rhun, J. E. Levasseur, C. Loisel, and M. Togola. 1991. Utilisation des bandes spectrales du vert et du rouge pour une meilleure évaluation des formations végétales actives. Sherbrooke: AUPELF-UREF. Télédétection et Cartographie.
  • Chen, J. M. 1996. “Evaluation of Vegetation Indices and a Modified Simple Ratio for Boreal Applications.” Canadian Journal of Remote Sensing 22 (3): 229–242. doi:10.1080/07038992.1996.10855178.
  • Chuvieco, E., and M. P. Martín. 1998. “Cartografía de grandes incendios forestales en la Península Ibérica a partir de imágenes NOAA-AVHRR.” 10.13039/501100000780.
  • Clandillon, S., P. Fraipont, and H. Yesou. 1995. “Assessment of the Future SPOT 4 MIR for Wetland Monitoring and Soil Moisture Analysis: Simulation Over the Ried Center Alsace (France).” Proceedings of the SPIE, 2585:102–111. 10.1117/12.227173.
  • Cleveland, W. S., and S. J. Devlin. 1988. “Locally Weighted Regression: An Approach to Regression Analysis by Local Fitting.” Journal of the American Statistical Association 83 (403): 596–610. doi:10.1080/01621459.1988.10478639.
  • Clevers, J. G. P. W. 1989. “Application of a Weighted Infrared-Red Vegetation Index for Estimating Leaf Area Index by Correcting for Soil Moisture.” Remote Sensing of Environment 29 (1): 25–37. doi:10.1016/0034-4257(89)90076-X.
  • Crippen, R. E. 1990. “Calculating the Vegetation Index Faster.” Remote Sensing of Environment 34 (1): 71–73. doi:10.1016/0034-4257(90)90085-Z.
  • Daouas, N. 2011. “A Study on Optimum Insulation Thickness in Walls and Energy Savings in Tunisian Buildings Based on Analytical Calculation of Cooling and Heating Transmission Loads.” Applied Energy 88 (1): 156–164. doi:10.1016/j.apenergy.2010.07.030.
  • Datt, B. 1998. “Remote Sensing of Chlorophyll A, Chlorophyll B, Chlorophyll A+b, and Total Carotenoid Content in Eucalyptus Leaves.” Remote Sensing of Environment 66 (2): 111–121. doi:10.1016/S0034-4257(98)00046-7.
  • Datt, B. 1999. “Remote Sensing of Water Content in Eucalyptus Leaves.” Australian Journal of Botany 47 (6): 909–923. doi:10.1071/bt98042.
  • Daughtry, C. S. T., C. L. L. Walthall, M. S. Kim, E. B. de Colstoun, and J. E. McMurtrey. 2000. “Estimating Corn Leaf Chlorophyll Concentration from Leaf and Canopy Reflectance.” Remote Sensing of Environment 74 (2): 229–239. doi:10.1016/S0034-4257(00)00113-9.
  • Deering, D. W., J. W. Rouse, R. H. Haas, and J. A. Schell. 1975. “Measuring ‘Forage production’ of Grazing Units from Landsat MSS Data.“ 10th International Symposium on Remote Sensing of Environment, Ann Arbor 2: 1169–1178.
  • Dixon, H., D. Lawler, A. Shamseldin, and P. Webster. 2006. “The Effect of Record Length on the Analysis of River Flow Trends in Wales and Central England.” IAHS-AISH Publication. https://www.semanticscholar.org/paper/The-effect-of-record-length-on-the-analysis-of-flow-Dixon-Lawler/cf1c26b5ce1b40d7a1aa3330853800c6aa435f04.
  • Drury, S. A. 2004. Image Interpretation in Geology. 3rd ed. Malden, MA: Routledge.
  • Escadafal, R., and A. R. Huete. 1991. “Etude Des Propriétés Spectrales Des Sols Arides Appliquée à l’amélioration Des Indices de Végétation Obtenus Par Télédétection. Comptes Rendus de l'Académie des Sciences 2: 1385–1391.
  • Estoque, R. C., and Y. Murayama. 2015. “Classification and Change Detection of Built-Up Lands from Landsat-7 ETM+ and Landsat-8 OLI/TIRS Imageries: A Comparative Assessment of Various Spectral Indices.” Ecological Indicators 56: 205–217. doi:10.1016/j.ecolind.2015.03.037.
  • Fensholt, R., and I. Sandholt. 2003. “Derivation of a Shortwave Infrared Water Stress Index from MODIS Near- and Shortwave Infrared Data in a Semiarid Environment.” Remote Sensing of Environment 87: 111–121. doi:10.1016/j.rse.2003.07.002.
  • Feyisa, G. L., H. Meilby, R. Fensholt, and S. R. Proud. 2014. “Automated Water Extraction Index: A New Technique for Surface Water Mapping Using Landsat Imagery.” Remote Sensing of Environment 140: 23–35. doi:10.1016/j.rse.2013.08.029.
  • Foga, S., P. L. Scaramuzza, S. Guo, Z. Zhu, R. D. Dilley, T. Beckmann, G. L. Schmidt, J. L. Dwyer, M. Joseph Hughes, and B. Laue. 2017. “Cloud Detection Algorithm Comparison and Validation for Operational Landsat Data Products.” Remote Sensing of Environment 194: 379–390. doi:10.1016/j.rse.2017.03.026.
  • Forkel, M., N. Carvalhais, J. Verbesselt, M. D. Mahecha, C. S. R. Neigh, and M. Reichstein. 2013. “Trend Change Detection in NDVI Time Series: Effects of Inter-Annual Variability and Methodology.” Remote Sensing 5 (5): 2113–2144. doi:10.3390/rs5052113.
  • Friedland, K. D., M. C. McManus, R. E. Morse, and J. S. Link. 2019. “Event Scale and Persistent Drivers of Fish and Macroinvertebrate Distributions on the Northeast US Shelf.” ICES Journal of Marine Science 76 (5): 1316–1334. doi:10.1093/icesjms/fsy167.
  • Gamon, J. A., and J. S. Surfus. 1999. “Assessing Leaf Pigment Content and Activity with a Reflectometer.” The New Phytologist 143 (1): 105–117. doi:10.1046/j.1469-8137.1999.00424.x.
  • Gao, B. C. 1996. “NDWI-A Normalized Difference Water Index for Remote Sensing of Vegetation Liquid Water from Space.” Remote Sensing of Environment 58 (3): 257–266. doi:10.1016/S0034-4257(96)00067-3.
  • García, M. J. L., and V. Caselles. 1991. “Mapping Burns and Natural Reforestation Using Thematic Mapper Data.” Geocarto International 6 (1): 31–37. doi:10.1080/10106049109354290.
  • Gitelson, A. A. 2004. “Wide Dynamic Range Vegetation Index for Remote Quantification of Biophysical Characteristics of Vegetation.” Journal of Plant Physiology 161 (2): 165–173. doi:10.1078/0176-1617-01176.
  • Gitelson, A. A., Y. Gritz, and M. N. Merzlyak. 2003. “Relationships Between Leaf Chlorophyll Content and Spectral Reflectance and Algorithms for Non-Destructive Chlorophyll Assessment in Higher Plant Leaves.” Journal of Plant Physiology 160 (3): 271–282. doi:10.1078/0176-1617-00887.
  • Gitelson, A. A., Y. J. Kaufman, and M. N. Merzlyak. 1996. “Use of a Green Channel in Remote Sensing of Global Vegetation from EOS-MODIS.” Remote Sensing of Environment 58 (3): 289–298. doi:10.1016/S0034-4257(96)00072-7.
  • Gitelson, A. A., Y. J. Kaufman, R. Stark, and D. Rundquist. 2002. “Novel Algorithms for Remote Estimation of Vegetation Fraction.” Remote Sensing of Environment 80 (1): 76–87. doi:10.1016/S0034-4257(01)00289-9.
  • Gitelson, A. A., and M. N. Merzlyak. 1994. “Spectral Reflectance Changes Associated with Autumn Senescence of Aesculus Hippocastanum L. and Acer Platanoides L. Leaves. Spectral Features and Relation to Chlorophyll Estimation.” Journal of Plant Physiology 143 (3): 286–292. doi:10.1016/S0176-1617(11)81633-0.
  • Gitelson, A. A., M. N. Merzlyak, and O. B. Chivkunova. 2001. “Optical Properties and Nondestructive Estimation of Anthocyanin Content in Plant Leaves.” Photochemistry and Photobiology 74 (1): 38–45. doi:10.1562/0031-865520010740038:OPANEO2.0.CO;2.
  • Goel, N. S., and W. Qin. 1994. “Influences of Canopy Architecture on Relationships Between Various Vegetation Indices and LAI and Fpar: A Computer Simulation.” Remote Sensing Reviews 10 (4): 309–347. doi:10.1080/02757259409532252.
  • Gong, P., R. Pu, G. S. Biging, and M. R. Larrieu. 2003. “Estimation of Forest Leaf Area Index Using Vegetation Indices Derived from Hyperion Hyperspectral Data.” IEEE Transactions on Geoscience and Remote Sensing 41 (6): 1355–1362. doi:10.1109/TGRS.2003.812910.
  • Gupta, K., A. Mukhopadhyay, S. Giri, A. Chanda, S. Datta Majumdar, S. Samanta, D. Mitra, R. N. Samal, A. K. Pattnaik, and S. Hazra. 2018. “An Index for Discrimination of Mangroves from Non-Mangroves Using LANDSAT 8 OLI Imagery.” MethodsX 5: 1129–1139. doi:10.1016/j.mex.2018.09.011.
  • Gustafsson, J. 2017. Single Case Studies Vs. Multiple Case Studies: A Comparative Study. Halmstad University. http://urn.kb.se/resolve?urn=urn:nbn:se:hh:diva-33017.
  • Haboudane, D., J. R. Miller, E. Pattey, P. J. Zarco-Tejada, and I. B. Strachan. 2004. “Hyperspectral Vegetation Indices and Novel Algorithms for Predicting Green LAI of Crop Canopies: Modeling and Validation in the Context of Precision Agriculture.” Remote Sensing of Environment 90 (3): 337–352. doi:10.1016/j.rse.2003.12.013.
  • Hall, D. K., G. A. Riggs, and V. V. Salomonson. 1995. “Development of Methods for Mapping Global Snow Cover Using Moderate Resolution Imaging Spectroradiometer Data.” Remote Sensing of Environment 54 (2): 127–140. doi:10.1016/0034-4257(95)00137-P.
  • Heiskanen, J. 2006. “Estimating Aboveground Tree Biomass and Leaf Area Index in a Mountain Birch Forest Using ASTER Satellite Data.” International Journal of Remote Sensing 27: 27. doi:10.1080/01431160500353858.
  • He, C., P. Shi, D. Xie, and Y. Zhao. 2010. “Improving the Normalized Difference Built-Up Index to Map Urban Built-Up Areas Using a Semiautomatic Segmentation Approach.” Remote Sensing Letters 1 (4): 213–221. doi:10.1080/01431161.2010.481681.
  • Hisdal, H., K. Stahl, L. M. Tallaksen, and S. Demuth. 2001. “Have Streamflow Droughts in Europe Become More Severe or Frequent?” International Journal of Climatology 21 (3): 317–333. doi:10.1002/joc.619.
  • Holben, B. N. 1986. “Characteristics of Maximum-Value Composite Images from Temporal AVHRR Data.” International Journal of Remote Sensing 7 (11): 1417–1434. doi:10.1080/01431168608948945.
  • Huete, A. R. 1988. “A Soil-Adjusted Vegetation Index (SAVI).” Remote Sensing of Environment 25 (3): 295–309. doi:10.1016/0034-4257(88)90106-X.
  • Huete, A. R., and H. Q. Liu. 1994. “An Error and Sensitivity Analysis of the Atmospheric- and Soil-Correcting Variants of the NDVI for the MODIS-EOS.” IEEE Transactions on Geoscience and Remote Sensing 32 (4): 897–905. doi:10.1109/36.298018.
  • Ibrahim, S., H. Balzter, K. Tansey, N. Tsutsumida, and R. Mathieu. 2018. “Estimating Fractional Cover of Plant Functional Types in African Savannah from Harmonic Analysis of MODIS Time-Series Data.” International Journal of Remote Sensing 39 (9): 2718–2745. doi:10.1080/01431161.2018.1430914.
  • Iris, Ç., and J. S. L. Lam. 2019. “A Review of Energy Efficiency in Ports: Operational Strategies, Technologies and Energy Management Systems.” Renewable and Sustainable Energy Reviews 112: 170–182. doi:10.1016/j.rser.2019.04.069.
  • Jacques, D. C., L. Kergoat, P. Hiernaux, E. Mougin, and P. Defourny. 2014. “Monitoring Dry Vegetation Masses in Semi-Arid Areas with MODIS SWIR Bands.” Remote Sensing of Environment 153: 40–49. doi:10.1016/j.rse.2014.07.027.
  • James, M. E., and S. N. V. Kalluri. 1994. “The Pathfinder AVHRR Land Data Set: An Improved Coarse Resolution Data Set for Terrestrial Monitoring.” International Journal of Remote Sensing 15 (17): 3347–3363. doi:10.1080/01431169408954335.
  • Jebb, A. T., L. Tay, W. Wang, and Q. Huang. 2015. “Time Series Analysis for Psychological Research: Examining and Forecasting Change.” Frontiers in Psychology 6: 727. doi:10.3389/fpsyg.2015.00727.
  • Jiang, Z., A. R. Huete, K. Didan, and T. Miura. 2008. “Development of a Two-Band Enhanced Vegetation Index Without a Blue Band.” Remote Sensing of Environment 112 (10): 3833–3845. doi:10.1016/j.rse.2008.06.006.
  • Jordan, C. F. 1969. “Derivation of Leaf-Area Index from Quality of Light on the Forest Floor.” Ecology 50 (4): 663–666. doi:10.2307/1936256.
  • Kanthi, N. S., and T. H. Purwanto. 2016. “Application of OpenStreetmap (OSM) to Support the Mapping Village in Indonesia.” IOP Conference Series: Earth and Environmental Science 47 (1): 012003. doi:10.1088/1755-1315/47/1/012003.
  • Karnieli, A., Y. J. Kaufman, L. Remer, and A. Wald. 2001. “AFRI — Aerosol Free Vegetation Index.” Remote Sensing of Environment 77 (1): 10–21. doi:10.1016/S0034-4257(01)00190-0.
  • Kaufman, Y. J., and D. Tanre. 1992. “Atmospherically Resistant Vegetation Index (ARVI) for EOS-MODIS.” IEEE Transactions on Geoscience and Remote Sensing 30 (2): 261–270. doi:10.1109/36.134076.
  • Kawamura, M., S. Jayamanna, and Y. Tsujiko. 1996. “Relation Between Social and Environmental Conditions in Colombo, Sri Lanka and the Urban Index Estimated by Satellite Remote Sensing Data.” 土木学会年次学術講演会講演概要集第1部 51st (Kyotsu Sesshon): 190–191.
  • Kerr, Y., W. Philippe, J. P. Wigneron, D. Steven, F. Cabot, B. Jacqueline, M. J. Escorihuela, et al. 2010. “The SMOS Mission: New Tool for Monitoring Key Elements of the Global Water Cycle.” Proceedings of the IEEE 98. 10.1109/JPROC.2010.2043032.
  • Key, C. H., and N. Benson. 2005. “Landscape Assessment (LA) Sampling and Analysis Methods.“ In FIREMON: Fire Effects Monitoring and Inventory System, LA 1-51, edited byLutes, D. C., R. E. Keane, J. F. Caratti, C. H. Key, N. Benson, S. Sutherland, and L. J. Ganji. Ogden, UT: USDA Forest Service, Rocky Mountain Research Station.
  • Khalili, A., P. van den Besselaar, and K. A. de Graaf. 2018. “Using Linked Open Geo Boundaries for Adaptive Delineation of Functional Urban Areas.” In The Semantic Web: ESWC 2018 Satellite Events, edited by A. Gangemi, A. L. Gentile, A. G. Nuzzolese, S. Rudolph, M. Maleshkova, H. Paulheim, J. Z. Pan, and M. Alam, 327–341. Vol. 11155 Lecture Notes in Computer Science. Cham: Springer International Publishing. doi:10.1007/978-3-319-98192-5_51.
  • Khan, N. M., V. V. Rastoskuev, Y. Sato, and S. Shiozawa. (2005). “Assessment of Hydrosaline Land Degradation by Using a Simple Approach of Remote Sensing Indicators.” Agricultural Water Management 77 (1): 96–109. Special Issue on Land and Water Use: Environmental Management Tools and Practices. doi:10.1016/j.agwat.2004.09.038.
  • Kim, Y., I. Kong, H. Park, H. J. Kim, I. J. Kim, M. J. Um, P. A. Green, and C. J. Vörösmarty. 2018. “Assessment of Regional Threats to Human Water Security Adopting the Global Framework: A Case Study in South Korea.” The Science of the Total Environment 637–638: 1413–1422. doi:10.1016/j.scitotenv.2018.04.420.
  • Klemas, V. 2011. “Remote Sensing of Wetlands: Case Studies Comparing Practical Techniques.” Journal of Coastal Research 27 (3): 418. doi:10.2112/JCOASTRES-D-10-00174.1.
  • Liu, H. Q., and A. R. Huete. 1995. “A Feedback Based Modification of the NDVI to Minimize Canopy Background and Atmospheric Noise.” IEEE Transactions on Geoscience and Remote Sensing 33 (2): 457–465. doi:10.1109/TGRS.1995.8746027.
  • Liu, X., J. Schnelle-Kreis, X. Zhang, J. Bendl, M. Khedr, G. Jakobi, B. Schloter-Hai, J. Hovorka, and R. Zimmermann. 2020. “Integration of Air Pollution Data Collected by Mobile Measurement to Derive a Preliminary Spatiotemporal Air Pollution Profile from Two Neighboring German-Czech Border Villages.” The Science of the Total Environment 722: 137632. doi:10.1016/j.scitotenv.2020.137632.
  • Li, B., L. Zhang, Q. Yan, and Y. Xue. 2014. “Application of Piecewise Linear Regression in the Detection of Vegetation Greenness Trends on the Tibetan Plateau.” International Journal of Remote Sensing 35 (4): 1526–1539. doi:10.1080/01431161.2013.878066.
  • Louhaichi, M., M. M. Borman, and D. E. Johnson. 2001. “Spatially Located Platform and Aerial Photography for Documentation of Grazing Impacts on Wheat.” Geocarto International 16 (1): 65–70. doi:10.1080/10106040108542184.
  • Lymburner, L., P. J. Beggs, and C. R. Jacobson. 2000. “Estimation of Canopy-Average Surface-Specific Leaf Area Using Landsat TM Data.” Photogrammetric Engineering and Remote Sensing 66 (2): 183–191.
  • Mahlein, A. K., T. Rumpf, Welke, P., H. W. Dehne, L. Plümer, U. Steiner , and E. C. Oerke. 2013. “Development of Spectral Indices for Detecting and Identifying Plant Diseases.” Remote Sensing of Environment 128: 21–30. doi:10.1016/j.rse.2012.09.019.
  • Manna, S., and B. Raychaudhuri. 2020. “Mapping Distribution of Sundarban Mangroves Using Sentinel-2 Data and New Spectral Metric for Detecting Their Health Condition.” Geocarto International 35 (4): 434–452. doi:10.1080/10106049.2018.1520923.
  • Masselot, P., F. Chebana, D. Bélanger, A. St-Hilaire, B. Abdous, P. Gosselin, and T. B. M. J. Ouarda. 2018. “Aggregating the Response in Time Series Regression Models, Applied to Weather-Related Cardiovascular Mortality.” The Science of the Total Environment 628–629: 217–225. doi:10.1016/j.scitotenv.2018.02.014.
  • Maxmax. 2015. “Enhanced Normalized Difference Vegetation Index.” https://www.maxmax.com/endvi.htm.
  • McFeeters, S. K. 1996. “The Use of the Normalized Difference Water Index (NDWI) in the Delineation of Open Water Features.” International Journal of Remote Sensing 17 (7): 1425–1432. doi:10.1080/01431169608948714.
  • Merzlyak, M. N., A. A. Gitelson, O. B. Chivkunova, and V. Y. Rakitin. 1999. “Non-Destructive Optical Detection of Pigment Changes During Leaf Senescence and Fruit Ripening.” Physiologia plantarum 106 (1): 135–141. doi:10.1034/j.1399-3054.1999.106119.x.
  • Molugaram, K., and G. S. Rao. 2017a. “Chapter 12 - Analysis of Time Series.” In Statistical Techniques for Transportation Engineering, edited by K. Molugaram and G. S. Rao, 463–489. Butterworth-Heinemann. doi:10.1016/B978-0-12-811555-8.00012-X.
  • Molugaram, K., and G. S. Rao. 2017b. “Chapter 6 - Correlation and Regression.” In Statistical Techniques for Transportation Engineering, edited by K. Molugaram and G. S. Rao, 293–329. Butterworth-Heinemann. doi:10.1016/B978-0-12-811555-8.00006-4.
  • Ng, W. T., P. Rima, K. Einzmann, M. Immitzer, C. Atzberger, and S. Eckert. 2017. “Assessing the Potential of Sentinel-2 and Pléiades Data for the Detection of Prosopis and Vachellia Spp. in Kenya.” Remote Sensing 9 (1): 74. doi:10.3390/rs9010074.
  • Otón, G., J. Lizundia-Loiola, M. L. Pettinari, and E. Chuvieco. 2021. “Development of a Consistent Global Long-Term Burned Area Product (1982–2018) Based on AVHRR-LTDR Data.” International Journal of Applied Earth Observation and Geoinformation 103: 102473. doi:10.1016/j.jag.2021.102473.
  • Penuelas, J., F. Baret, and I. Filella. 1995. “Semi-Empirical Indices to Assess Carotenoids/chlorophyll-A Ratio from Leaf Spectral Reflectance.” Photosynthetica 31: 221–230.
  • Peñuelas, J., J. A. Gamon, A. L. Fredeen, J. Ángel Merino, and C. B. Field. 1994. “Reflectance Indices Associated with Physiological Changes in Nitrogen- and Water-Limited Sunflower Leaves.” Remote Sensing of Environment 48 (2): 135–146. doi:10.1016/0034-4257(94)90136-8.
  • Perry, C. R., and L. F. Lautenschlager. 1984. “Functional Equivalence of Spectral Vegetation Indices.” Remote Sensing of Environment 14 (1): 169–182. doi:10.1016/0034-4257(84)90013-0.
  • Pinty, B., and M. M. Verstraete. 1992. “GEMI: A Non-Linear Index to Monitor Global Vegetation from Satellites.” Vegetatio 101 (1): 15–20. doi:10.1007/BF00031911.
  • Politi, E., M. E. J. Cutler, and J. S. Rowan. 2012. “Using the NOAA Advanced Very High Resolution Radiometer to Characterise Temporal and Spatial Trends in Water Temperature of Large European Lakes.” Remote Sensing of Environment 126: 1–11. doi:10.1016/j.rse.2012.08.004.
  • Qi, J., A. Chehbouni, A. R. Huete, Y. H. Kerr, and S. Sorooshian. 1994. “A Modified Soil Adjusted Vegetation Index.” Remote Sensing of Environment 48 (2): 119–126. doi:10.1016/0034-4257(94)90134-1.
  • Rahman, H., and G. Dedieu. 1994. “SMAC: A Simplified Method for the Atmospheric Correction of Satellite Measurements in the Solar Spectrum.” International Journal of Remote Sensing 15 (1): 123–143. doi:10.1080/01431169408954055.
  • Rasul, A., H. Balzter, G. R. Faqe Ibrahim, H. M. Hameed, J. Wheeler, B. Adamu, S. Ibrahim, and P. M. Najmaddin. 2018. “Applying Built-Up and Bare-Soil Indices from Landsat 8 to Cities in Dry Climates.” Land 7 (3): 81. doi:10.3390/land7030081.
  • Rock, B. N., J. E. Vogelmann, D. L. Williams, A. F. Vogelmann, and T. Hoshizaki. 1986. “Remote Detection of Forest Damage: Plant Responses to Stress May Have Spectral ‘Signatures’ That Could Be Used to Map, Monitor, and Measure Forest Damage.” BioScience 36 (7): 439–445. doi:10.2307/1310339.
  • Roger, J. C., A. Santamaria Artigas, J. P. Ray, J. L. Villaescusa Nadal, F. V. Eric, and S. Devadiga. 2021. “LTDR AVHRR Products (Version 5) User’s Guide.”
  • Rondeaux, G., M. Steven, and F. Baret. 1996. “Optimization of Soil-Adjusted Vegetation Indices.” Remote Sensing of Environment 55 (2): 95–107. doi:10.1016/0034-4257(95)00186-7.
  • Roujean, J. L., and F. M. Breon. 1995. “Estimating PAR Absorbed by Vegetation from Bidirectional Reflectance Measurements.” Remote Sensing of Environment 51 (3): 375–384. doi:10.1016/0034-4257(94)00114-3.
  • Rouse, J. W., R. H. Haas, J. A. Schell, and D. W. Deering. 1974. Monitoring Vegetation Systems in the Great Plains with Erts Third Earth Resources Technology Satellite-1 Symposium, Washington. 309. Vol. 1. Washington: NASA Special Publication.
  • Sa’adi, Z., Z. M. Yaseen, A. A. Farooque, N. A. Mohamad, M. K. I. Muhammad, and Z. Iqbal. 2023. “Long-Term Trend Analysis of Extreme Climate in Sarawak Tropical Peatland Under the Influence of Climate Change.” Weather and Climate Extremes 40: 100554. doi:10.1016/j.wace.2023.100554.
  • Savitzky, A., and M. J. E. Golay. 1964. “Smoothing and Differentiation of Data by Simplified Least Squares Procedures.” Analytical Chemistry 36 (8): 1627–1639. doi:10.1021/ac60214a047.
  • Scudiero, E., T. H. Skaggs, and D. L. Corwin. 2014. “Regional Scale Soil Salinity Evaluation Using Landsat 7, Western San Joaquin Valley, California, USA.” Geoderma Regional 2–3: 82–90. doi:10.1016/j.geodrs.2014.10.004.
  • Segal Donald, B. 1982. “Theoretical Basis for Differentiation of Ferric-Iron Bearing Minerals Using Landsat MSS Data.” In Proceedings of the International Symposium on Remote Sensing of Environment, Fort Worth, 6–10:949–951.
  • Silleos, N. G., T. K. Alexandridis, I. Z. Gitas, and K. Perakis. 2006. “Vegetation Indices: Advances Made in Biomass Estimation and Vegetation Monitoring in the Last 30 Years.” Geocarto International 21 (4): 21–28. doi:10.1080/10106040608542399.
  • Smith, A. M. S., M. J. Wooster, N. A. Drake, F. M. Dipotso, M. J. Falkowski, and A. T. Hudak. 2005. “Testing the Potential of Multi-Spectral Remote Sensing for Retrospectively Estimating Fire Severity in African Savannahs.” Remote Sensing of Environment 97 (1): 92–115. doi:10.1016/j.rse.2005.04.014.
  • Sobrino, J. A., and N. Raissouni. 2000. “Toward Remote Sensing Methods for Land Cover Dynamic Monitoring: Application to Morocco.” International Journal of Remote Sensing 21 (2): 353–366. doi:10.1080/014311600210876.
  • Sorokhtin, O. G., G. V. Chilingar, and L. F. Khilyuk. 2007. “Global Warming and Global Cooling: Evolution of Climate on Earth.“ In Developments in Earth and Environmental Sciences, edited by Sorokhtin, O. G., G. V. Chilingar, and L. F. Khilyuk, Vol. 5, pp. 332. Amsterdam: Elsevier.
  • Sripada, R. P. 2005. Determining In-Season Nitrogen Requirements for Corn Using Aerial Color-Infrared Photography. Faculty of North Carolina State University. http://www.lib.ncsu.edu/resolver/1840.16/4200.
  • Thiam, A. K. 1998. “Geographic Information Systems and Remote Sensing Methods for Assessing and Monitoring Land Degradation in the Sahel Region: The Case of Southern Mauritania.” Ph.D. Thesis.
  • Toca, L., K. Morrison, R. Artz, A. Gimona, and T. Quaife. 2022. “High Resolution C-Band SAR Backscatter Response to Peatland Water Table Depth and Soil Moisture: A Laboratory Experiment.” International Journal of Remote Sensing 43 (14): 5231–5251. doi:10.1080/01431161.2022.2131478.
  • Toté, C., E. Swinnen, S. Sterckx, D. Clarijs, C. Quang, and R. Maes. 2017. “Evaluation of the SPOT/VEGETATION Collection 3 Reprocessed Dataset: Surface Reflectances and NDVI.” Remote Sensing of Environment 201: 219–233. doi:10.1016/j.rse.2017.09.010.
  • Tucker, C. J. 1979. “Red and Photographic Infrared Linear Combinations for Monitoring Vegetation.” Remote Sensing of Environment 8 (2): 127–150. doi:10.1016/0034-4257(79)90013-0.
  • Uwe, M. W., L. Pessiot, and O. Devignot. 2016. Sen2cor Configuration and User Manual. Darmstadt, Germany: Telespazio VEGA Deutschland GmbH.
  • Vermote, E. F., D. Tanre, J. L. Deuze, M. Herman, and J. -J. Morcette. 1997. “Second Simulation of the Satellite Signal in the Solar Spectrum, 6S: An Overview.” IEEE Transactions on Geoscience and Remote Sensing 35 (3): 675–686. doi:10.1109/36.581987.
  • Vincini, M., E. Frazzi, and P. D’Alessio. 2007. “Comparison of Narrow-Band and Broad-Band Vegetation Indices for Canopy Chlorophyll Density Estimation in Sugar Beet.” Precision Agriculture ’07. Papers Presented at the 6th European Conference on Precision Agriculture Skiathos, 189–196.
  • Vogelmann, J. E., G. Xian, C. Homer, and B. Tolk. 2012. “Monitoring Gradual Ecosystem Change Using Landsat Time Series Analyses: Case Studies in Selected Forest and Rangeland Ecosystems.” Remote Sensing of Environment 122: 92–105. doi:10.1016/j.rse.2011.06.027.
  • Wang, J., A. Botterud, R. Bessa, H. Keko, L. Carvalho, D. Issicaba, J. Sumaili, and V. Miranda. 2011. “Wind Power Forecasting Uncertainty and Unit Commitment.” Applied Energy 88 (11): 4014–4023. doi:10.1016/j.apenergy.2011.04.011.
  • Wang, C., J. Chen, J. Wu, Y. Tang, P. Shi, T. A. Black, and K. Zhu. 2017. “A Snow-Free Vegetation Index for Improved Monitoring of Vegetation Spring Green-Up Date in Deciduous Ecosystems.” Remote Sensing of Environment 196: 1–12. doi:10.1016/j.rse.2017.04.031.
  • Wang, J., J. Ding, D. Yu, X. Ma, Z. Zhang, X. Ge, D. Teng, et al. 2019. “Capability of Sentinel-2 MSI Data for Monitoring and Mapping of Soil Salinity in Dry and Wet Seasons in the Ebinur Lake Region, Xinjiang, China.” Geoderma 353: 172–187. doi:10.1016/j.geoderma.2019.06.040.
  • Wang, L., and J. J. Qu. (2007)). “NMDI: A Normalized Multi-Band Drought Index for Monitoring Soil and Vegetation Moisture with Satellite Remote Sensing”. Geophysical Research Letters 34: 20. 10.1029/2007GL031021.
  • Warren Liao, T. . 2005. “Clustering of Time Series Data—A Survey.” Pattern Recognition 38 (11): 1857–1874. doi:10.1016/j.patcog.2005.01.025.
  • Waser, L. T., M. Küchler, K. Jütte, and T. Stampfer. 2014. “Evaluating the Potential of WorldView-2 Data to Classify Tree Species and Different Levels of Ash Mortality.” Remote Sensing 6 (5): 4515–4545. doi:10.3390/rs6054515.
  • Witt, R., L. Loos, and A. Zipf. 2021. “Analysing the Impact of Large Data Imports in OpenStreetmap.” ISPRS International Journal of Geo-Information 10 (8): 528. doi:10.3390/ijgi10080528.
  • Xu, H. 2006. “Modification of Normalised Difference Water Index (NDWI) to Enhance Open Water Features in Remotely Sensed Imagery.” International Journal of Remote Sensing 27 (14): 3025–3033. doi:10.1080/01431160600589179.
  • Xu, H. 2008. “A New Index for Delineating Built‐up Land Features in Satellite Imagery.” International Journal of Remote Sensing 29 (14): 4269–4276. doi:10.1080/01431160802039957.
  • Yan, S., X. Yao, D. Zhu, D. Liu, L. Zhang, G. Yu, B. Gao, J. Yang, and W. Yun. 2021. “Large-Scale Crop Mapping from Multi-Source Optical Satellite Imageries Using Machine Learning with Discrete Grids.” International Journal of Applied Earth Observation and Geoinformation 103: 102485. doi:10.1016/j.jag.2021.102485.
  • Zarco-Tejada, P. J., and S. L. Ustin. 2001. “Modeling Canopy Water Content for Carbon Estimates from MODIS Data at Land EOS Validation Sites.” https://digital.csic.es/handle/10261/10642.
  • Zha, Y., J. Gao, and S. Ni. 2003. “Use of Normalized Difference Built-Up Index in Automatically Mapping Urban Areas from TM Imagery.” International Journal of Remote Sensing 24 (3): 583–594. doi:10.1080/01431160304987.
  • Zhao, H., and X. Chen. 2005. “Use of Normalized Difference Bareness Index in Quickly Mapping Bare Areas from TM/ETM+.” In Proceedings. 2005 IEEE International Geoscience and Remote Sensing Symposium, 3:1666–1668. 10.1109/IGARSS.2005.1526319.

Reprints and Corporate Permissions

Please note: Selecting permissions does not provide access to the full text of the article, please see our help page How do I view content?

To request a reprint or corporate permissions for this article, please click on the relevant link below:

Academic Permissions

Please note: Selecting permissions does not provide access to the full text of the article, please see our help page How do I view content?

Obtain permissions instantly via Rightslink by clicking on the button below:

If you are unable to obtain permissions via Rightslink, please complete and submit this Permissions form. For more information, please visit our Permissions help page.