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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, 2023, Vol. 20, No. 2, pp. 60-74

Analysis of the possibility of using different spatial resolution data for objects monitoring

A.V. Kashnitskii 1 , E.A. Loupian 1 , D.E. Plotnikov 1 , V.A. Tolpin 1 
1 Space Research Institute RAS, Moscow, Russia
Accepted: 04.04.2023
DOI: 10.21046/2070-7401-2023-20-2-60-74
The paper analyzes the suitability of using low spatial resolution data when monitoring objects on the basis of characteristics averaged within their boundaries. For this purpose the influence of spatial resolution of remote sensing data on the average values of NDVI (Normalized Difference Vegetation Index) within the boundaries of agricultural fields depending on their area was studied. Three datasets derived from information from MODIS (Moderate Resolution Imaging Spectroradiometer), KMSS (Satellite Multiband Imaging System), and MSI (MultiSpectral Instrument) instruments with spatial resolutions of 250, 60, and 10 m/pixel, respectively, were used. A time series of reconstructed daily cloudless images was used for each set. A sample of agricultural fields in different regions of Russia was taken. For each field, the average NDVI value for each data set was calculated and a correlation analysis of the values obtained from different data sets was carried out. The results of the analysis, when considering the whole growing season, showed general high consistency: even for fields of less than 10 ha the Pearson correlation coefficient values exceeded 0.75 for KMSS – MSI and MODIS – MSI pairs and 0.85 for MODIS – KMSS pair. However, the Pearson correlation coefficient drops significantly when analyzing data at certain periods of the year: at the beginning of the season in the MODIS – MSI pair for fields smaller than 2.5 ha to 0.45, for fields from 2.5 to 5 ha to 0.58. Further, the minimal value for the period increases uniformly with the increase of the fields and at the area of more than 15 ha for all weeks makes more than 0.82. Thus, it was concluded that for fields of more than 10–15 ha the course of average NDVI has similar trends, according to the data with spatial resolution of 250, 60 and 10 m/pixel. For smaller fields, there are large differences in the period of lowest NDVI values corresponding to plowing. The exact criterion for the suitability of low spatial resolution data for the analysis of objects of a certain area depends on the task and the period of the year.
Keywords: KMSS, MSI, MODIS, remote sensing, correlation analysis, spatial resolution effects, NDVI index progress, satellite monitoring, agricultural fields
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References:

  1. Burtsev M. A., Uspenskiy S. A., Kramareva L. S., Antonov V. N., Kalashnikov A. V., Balashov I. V., Kashnitskii A. V., Loupian E. A., Matveev A. M., Proshin A. A., Actual features and evolution prospects of the SRC “Planeta” distributed data operation united system, Sovremennye problemy distantsionnogo zondirovaniya Zemli iz kosmosa, 2019, Vol. 16, No. 3, pp. 198–212 (in Russian), DOI: 10.21046/2070-7401-2019-16-3-198-212.
  2. Denisov P. V., Sereda I. I., Troshko K. A., Loupian E. A., Plotnikov D. E., Tolpin V. A., Opportunities and experience of operational remote monitoring of winter crops condition in Russia, Sovremennye problemy distantsionnogo zondirovaniya Zemli iz kosmosa, 2021, Vol. 18, No. 2, pp. 171–185 (in Russian), DOI: 10.21046/2070-7401-2021-18-2-171-185.
  3. Elkina E. S., Egorov V. A., Plotnikov D. E., Samofal E. V., Bartalev S. A., Patil V. C., Sunil J. K., Chavan V. S., Development of satellite monitoring methods for sugarcane crop condition assessment in Peninsular India, Sovremennye problemy distantsionnogo zondirovaniya Zemli iz kosmosa, 2019, Vol. 16, No. 5, pp. 159–173 (in Russian), DOI: 10.21046/2070-7401-2019-16-5-159-173.
  4. Loupian E. A., Proshin A. A., Burtsev M. A., Kashnitskii A. V., Balashov I. V., Bartalev S. A., Konstantinova A. M., Kobets D. A., Mazurov A. A., Marchenkov V. V., Matveev A. M., Radchenko M. V., Sychugov I. G., Tolpin V. A., Uvarov I. A., Experience of development and operation of the “IKI-Monitoring” center for collective use of systems for archiving, processing and analyzing satellite data, Sovremennye problemy distantsionnogo zondirovaniya Zemli iz kosmosa, 2019, Vol. 16, No. 3, pp. 151–170 (in Russian), DOI: 10.21046/2070-7401-2019-16-3-151-170.
  5. Loupian E. A., Konstantinova A. M., Kashnitskii A. V., Ermakov D. M., Savorskiy V. P., Panova O. Yu., Bril A. A., The possibilities of organizing long-term remote monitoring of large sources of anthropogenic pollution to assess their impact on the environment, Sovremennye problemy distantsionnogo zondirovaniya Zemli iz kosmosa, 2022, Vol. 19, No. 1, pp. 193–213 (in Russian), DOI: 10.21046/2070-7401-2022-19-1-193-213.
  6. Plotnikov D. E., Elkina E. S., Dunaieva E. A., Khvosikov S. A., Loupian E. A., Bartalev S. A. (2020a), Development of the method for automatic winter crops mapping by means of remote sensing aimed at crops state assessment over the Republic of Crimea, Taurida herald of the agrarian sciences, 2020, No. 1(21), pp. 64–83 (in Russian), DOI: 10.33952/2542-0720-2020-1-21-64-83.
  7. Plotnikov D. E., Kolbudaev P. A., Zhukov B. S., Matveev A. M., Bartalev S. A., Egorov V. A., Kashnitskii A. V., Proshin A. A. (2020b), The collection of multispectral KMSS-M (Meteor-M No. 2) satellite data aimed at quantitative assessment of the Earth surface, Sovremennye problemy distantsionnogo zondirovaniya Zemli iz kosmosa, 2020, Vol. 7, No. 7, pp. 276–282 (in Russian), DOI: 10.21046/2070-7401-2020-17-7-276–282.
  8. Cleveland W. S., Robust Locally Weighted Regression and Smoothing Scatterplots, J. American Statistical Association, 1979, Vol. 74, Art. No. 368, pp. 829–836, DOI: 10.2307/2286407.
  9. Denisov P. V., Kashnitskii A. V., Loupian E. A., Sereda I. I., Tolpin V. A., Troshko K. A., Possibilities of Vega satellite monitoring services for arable land use assessment on the example of Smolensk region, IOP Conf. Ser.: Earth and Environmental Science, 2021, Vol. 723, Art. No. 032072, DOI: 10.1088/1755-1315/723/3/032072.
  10. Kolbudaev P. A., Plotnikov D. E., Loupian E. A., Proshin A. A., Matveev A. M., The methods and automatic technology aimed at imagery georeferencing, cloud screening, atmospheric and radiometric correction of KMSS-M satellite data, E3S Web Conf., 2021, Vol. 333, Art. No. 01006, https://doi.org/10.1051/e3sconf/202133301006.
  11. Loupian E. A., Bourtsev M. A., Proshin A. A., Kashnitskii A. V., Balashov I. V., Bartalev S. A., Konstantinova A. M., Kobets D. A., Radchenko M. V., Tolpin V. A., Uvarov I. A., Usage Experience and Capabilities of the VEGA-Science System, Remote Sensing, 2022, Vol. 14, No. 1, Art. No. 77, DOI: 10.3390/rs14010077.
  12. Plotnikov D. E., Loupian E. A., Kolbudaev P. A., Proshin A. A., Matveev A. M., Daily surface reflectance reconstruction using LOWESS on the example of various satellite systems, VIII Intern. Conf. Information Technology and Nanotechnology (ITNT), 2022, pp. 1–5, DOI: 10.1109/ITNT55410.2022.9848630.