Журнал

About Editorial Board Information for authors and reviewers Publication ethics Contacts User Account: send / review a manuscript
Archive
Volume 21, 2024
Number 1 Number 2 Number 3 Number 4 Number 5
Volume 20, 2023
Number 1 Number 2 Number 3 Number 4 Number 5 Number 6
Volume 19, 2022
Number 1 Number 2 Number 3 Number 4 Number 5 Number 6
Volume 18, 2021
Number 1 Number 2 Number 3 Number 4 Number 5 Number 6
Volume 17, 2020
Number 1 Number 2 Number 3 Number 4 Number 5 Number 6 Number 7
Volume 16, 2019
Number 1 Number 2 Number 3 Number 4 Number 5 Number 6
Volume 15, 2018
Number 1 Number 2 Number 3 Number 4 Number 5 Number 6 Number 7
Volume 14, 2017
Number 1 Number 2 Number 3 Number 4 Number 5 Number 6 Number 7
Volume 13, 2016
Number 1 Number 2 Number 3 Number 4 Number 5 Number 6
Volume 12, 2015
Number 1 Number 2 Number 3 Number 4 Number 5 Number 6
Volume 11, 2014
Number 1 Number 2 Number 3 Number 4
Volume 10, 2013
Number 1 Number 2 Number 3 Number 4
Volume 9, 2012
Number 1 Number 2 Number 3 Number 4 Number 5
Volume 8, 2011
Number 1 Number 2 Number 3 Number 4
Volume 7, 2010
Number 1 Number 2 Number 3 Number 4
Issue 6, 2009
Volume 1 Volume 2
Issue 5, 2008
Volume 1 Volume 2
Issue 4, 2007
Volume 1 Volume 2
Issue 3, 2006
Volume 1 Volume 2
Issue 2, 2005
Volume 1 Volume 2
Issue 1, 2004
Volume 1
Search
Find:
русский
ISSN 2070-7401 (Print), ISSN 2411-0280 (Online)
Sovremennye problemy distantsionnogo zondirovaniya Zemli iz kosmosa
CURRENT PROBLEMS IN REMOTE SENSING OF THE EARTH FROM SPACE

  

Sovremennye problemy distantsionnogo zondirovaniya Zemli iz kosmosa, 2017, Vol. 14, No. 3, pp. 173-181

Methodological and informational bases of water availability estimation of a territory by remote sensing and GIS means

E.A. Dunaeva 1 
1 Research Institute of Agriculture of Crimea, Simferopol, Russia
Accepted: 16.05.2017
DOI: 10.21046/2070-7401-2017-14-3-173-181
The aim of the work is to develop and test the improved methodology of water availability estimation in the steppe part of the Crimean Peninsula. GIS and remote sensing data were used to obtain more accurate information on water resource potential of the region. The work is especially relevant due to the necessity to redirect the Crimean water complex to the local water resources, to establish and map the water resource potential of the territory. To achieve these objectives, Earth remote sensing data such as results of satellite image interpretation, monitoring materials of ecosystems development and water availability parameters – NDVI, NDDI, etc. – were used. With the use of open GIS software, these data enabled to identify thematic layers, define the basic elements of water balance of the territory and clarify the indicators of water resources availability of the steppe part of the Crimean Peninsula with subsequent graphic visualization. The created database of water availability criteria has more than 20 indicators with characteristics, calculation formulae, ranges of variation of parameters, advantages and limitations of use. The database can serve as the basis for a geodatabase and can be used as part of a decision support system for mitigating the effects of drought.
Keywords: GIS, remote sensing, SPI, AI, NDVI, NDDI, water availability, precipitation, evaporation, Crimea
Full text

References:

  1. Bartalev S.A., Loupian E.A., Issledovaniya i razrabotki IKI RAN po razvitiyu metodov sputnikovogo monitoringa rastitel'nogo pokrova (R&D on methods for satellite monitoring of vegetation by the Russian Academy of Sciences’ Space Research Institute), Issledovanie Zemli iz kosmosa, 2013, Vol. 10, No. 1, pp. 197–214.
  2. Loupian E.A., Bartalev S.A., Krasheninnikova Yu.S., Nablyudenie anomal'no rannego razvitiya sel'skokhozyaistvennykh kul'tur v yuzhnykh regionakh Rossii vesnoi 2016 goda na osnove dannykh distantsionnogo monitoringa (Observing an abnormally early development of crops in the southern regions of Russia in spring 2016 using remote monitoring data), Sovremennye problemy distantsionnogo zondirovaniya Zemli iz kosmosa, 2016,
  3. http://msh.rk.gov.ru/file/postanovlenie_soveta_ministrov_respubliki_krim_ot423.pdf .
  4. Savin I., Loupian E., Bartalev S., Operativnyi sputnikovyi monitoring sostoyaniya posevov sel'skokhozyaistvennykh kul'tur v Rossii (Efficient Space Monitoring of Crops in Russia), Geomatika, 2011, No. 2, pp. 69–76.
  5. Strashnaya A.I., Bartalev S.A., Maksimenkova T.A., Chub O.V., Tolpin V.A., Plotnikov D.E., Bogomolova N.A., Agrometeorologicheskaya otsenka sostoyaniya ozimykh zernovykh kul'tur v period prekrashcheniya vegetatsii s ispol'zovaniem nazemnykh i sputnikovykh dannykh na primere Privolzhskogo federal'nogo okruga (Agrometeorological evaluation of the state of winter crops in the period of cessation of the growing season using ground and satellite data on the example of the Privolzhskiy Federal District, Trudy Gidrometeorologicheskogo nauchno-issledovatel'skogo tsentra Rossiiskoi Federatsii, 2014, No. 351, pp. 85–107.
  6. Strashnaya A.I., Tishtshenko V.A., Bogomolova N.A., Pavlova K.I., Tebuev H.H., Agrometeorologicheskie usloviya i prognozirovanie urozhainosti semyan podsolnechnika v Privolzhskom federal'nom okruge (Agrometeorological conditions and forecasting of productivity of sunflower seeds in the Privolzhskiy Federal District), Trudy Gidrometeorologicheskogo nauchno-issledovatel'skogo tsentra Rossiiskoi Federatsii, 2016, No. 359, pp. 142–160.
  7. Strashnaya A.I., Tarasova L.L., Bogomolova N.A., Maksimenkova T.A., Bereza O.V., Prognozirovanie urozhainosti zernovykh i zernobobovykh kul'tur v tsentral'nykh chernozemnykh oblastyakh na osnove kompleksirovaniya nazemnykh i sputnikovykh dannykh (Prediction of the yield of grain and leguminous crops in central black soil areas on the basis of complexation of ground and satellite data), Trudy Gidrometeorologicheskogo nauchno-issledovatel'skogo tsentra Rossiiskoi Federatsii, 2015, No. 353, pp. 128–153.
  8. Tolpin V.A., Bartalev S.A., Burtsev M.A., Efremov V.Yu., Loupian E.A., Mazurov A.A., Matveev A.M., Proshin A.A., Flitman E.V., Otsenka sostoyaniya sel’skokhozyaistvennykh kul’tur na osnove mezhgodovoi dinamiki s ispol’zovaniem dannykh MODIS (Interannual dynamics based tstimation of crops conditions by MODIS data), Sovremennye problemy distantsionnogo zondirovaniya Zemli iz kosmosa, 2007, Issue 4, No. 2, pp. 380–389.
  9. Tolpin V.A., Loupian E.A., Bartalev S.A., Plotnikov D.E., Matveev A.M., Vozmozhnosti analiza sostoyaniya sel’skokhozyaistvennoi rastitel’nosti s ispol’zovaniem sputnikovogo servisa “VEGA” (Possibilities of agricultural vegetation condition analysis with the “VEGA” satellite service), Atmospheric and Oceanic Optics, 2014, Vol. 27, No. 7 (306), pp. 581–586.
  10. Shcherbenko E.V., Distantsionnye metody vyyavleniya sel'skokhozyaistvennoi zasukhi (Remote sensing identification of agricultural drought), Sovremennye problemy distantsionnogo zondirovaniya Zemli iz kosmosa, 2007, Issue 4, Vol. 2, pp. 408–419.
  11. Shcherbenko E.V., Shorokhova M.A., Dronin N.M., Skabelkin Yu.A., Obnaruzhenie zasukhi po dannym kosmicheskikh s"emok (Drought detection according to satellite imagery), ArcReview, 2004, No. 2, pp. 8–9.
  12. Alexandridis T.K., Cherif I., Chemin Y., Silleos G.N., Stavrinos E., Zalidis G.C., Integrated methodology for estimating water use in Mediterranean agricultural areas, Remote Sensing, 2009, Vol. 1 (3), pp. 445–465.
  13. Alexandridis T.K., Zalidis G.C., Silleos N.G., Mapping irrigated area in Mediterranean basins using low cost satellite Earth Observation, Computers and Electronics in Agriculture, 2008, Vol. 64 (2), pp. 93–103.
  14. Bastiaanssen W.G.M., Karimi P., Rebelo L.-M., Duan Z., Senay G., Muttuwatte L., Smakhtin V., Earth Observation Based Assessment of the Water Production and Water Consumption of Nile Basin Agro-Ecosystems, Remote Sensing, 2014, Vol. 6 (11), pp. 10306–10334.
  15. Hu G., Jia L., Menenti M., Comparison of MOD16 and LSA-SAF MSG evapotranspiration products over Europe for 2011, Remote Sensing of Environment, 2015, Vol. 15, pp. 510–526.
  16. Karimi P., Bastiaanssen W.G.M., Spatial evapotranspiration, rainfall and land use data in water accounting – Part 1: Review of the accuracy of the remote sensing data, Hydrology and Earth System Sciences Discussions, 2013, Vol. 15, pp. 507–532.
  17. Labbassi K., Akdim N., Alfieri S.M., Menenti M., Observation and Modelling of Soil Water Content Towards Improved Performance Indicators of Large Irrigation Schemes, EGU General Assembly, Geophysical Research Abstracts, Austria, 2014, Vol. 16, p. 14994.
  18. Menenti M., Jia L., Mousivand A., Hu G., Zheng C., Lu J., Evaluation of ET data products: Parameterizations, rate limiting process and influential surface properties, Geoscience and Remote Sensing Symposium (IGARSS), 2016 IEEE International, 2016, pp. 214–217
  19. Mucher S., Roerink G., Franke J., Suomalainen J., Kooistra L., Monitoring agricultural crop growth: comparison of high spatial-temporal satellite imagery versus UAV-based imaging spectrometer time series measurements, EGU General Assembly Conference Abstracts, 2014, Vol. 16, p. 15788.
  20. Popovych V., Dunaieva Ie., Monitoring and Evaluation of Water Availability of the South of Ukraine and Russian Federation with Usage of the Standardized Precipitation Index, International Journal of Engineering Research & Technology (IJERT), 2014, Vol. 3, Issue 9, pp. 24–27.
  21. Roerink G.J., Menenti M., Soepboer W., Su Z., Assessment of climate impact on vegetation dynamics by using remote sensing, Physics and Chemistry of the Earth, Parts A/B/C, 2003, Vol. 28 (1), Issues 1–3, pp. 103–109.
  22. Seppelt R., Voinov A., Optimization Methodology for Land Use Patterns Using Spatial Explicit Landscape Models, Ecological Modeling, 2002, Vol. 151/2–3, pp. 125–145.
  23. van Eekelen M.W., Bastiaanssen W.G.M., Jarmain C., Jackson B., Fereira F., van der Zaag P., Okello A.S., Bosch J., Dyeh P., Bastidas-Obando ., Dost R.J.J., Luxemburg W.M.J., A novel approach to estimate direct and indirect water withdrawals from satellite measurements: A case study from the Incomati basin, Agriculture Ecosystems & Environment, 2015, Vol. 200, pp. 126–142.
  24. Voinov A., Bousquet F., Modelling with stakeholders, Environmental Modelling & Software, 2010, Vol. 25, pp. 1268–1281.