Sovremennye problemy distantsionnogo zondirovaniya Zemli iz kosmosa, 2014, Vol. 11, No. 3, pp. 180-192
On possibilities of arable lands quality evaluation in Baksan District of Kabardino-Balkaria based on satellite service VEGA
I.Yu. Savin
1,2 , E.R. Tanov
2
1 V.V. Dokuchaev Soil Science Institute, Moscow, Russia
2 Peoples’ Friendship University of Russia, Moscow, Russia
The new approach for evaluating the quality of arable lands was developed based on the use of MODIS satellite data. The essence of the approach consists in expert analysis of the curves of vegetation index NDVI for the last 10- 12 years separately for different groups of crops and also the year-to-year variability of the seasonal maximum of NDVI, whose value is used as an indicator of the state of crops and crop yield on separate fields. By the nature of the vegetation index NDVI profiles, they all were expertly classified into groups characterizing winter, early spring and late spring crops. The developed approach for evaluating the quality of arable lands was approved on the example of the Baksan region of Kabardino-Balkaria. Analysis was carried out for all arable parcels of the region, whose masks were obtained by the visual deciphering of their boundaries based on Landsat satellite data. The NDVI time profiles were obtained with the use of the satellite service VEGA. On the basis of the developed method, all fields of the region were ranked by the quality of arable lands. Obtained data can be used in cadastre lands evaluation, and also for optimization of arrangement of basic agricultural crops in the republic. The developed approach can be used also for other regions and subjects of the Russian Federation.
Keywords: land quality evaluation, satellite service VEGA, Kabardino-Balkaria
Full textReferences:
- Loupian E.A., Savin I.Yu., Bartalev S.A., Tolpin V.A., Balashov I.V., Plotnikov D.E. Sputnikovy servis monitoring sostoyania rastitelnosti (“Vega”) (Satellite service of monitoring the state of vegetation (“Vega”)), Sovremennye problemy distantsionnogo zondirovaniya Zemli iz kosmosa, 2011, Vol. 8, No. 1, pp. 190-198.
- Pochvennaya karta Kabardino-Balkarskoy SSR. Maschtab 1:200000 (Soil Map of Kabardino-Balkarskaya SSR). Scale 1:200000. – GUGK, 1985.
- Savin I.Yu., Simakova M.S. Sputnikovye tekhnologii dlia inventarizatsii I monitoring pochv v Rossii (Satellite technologies for soil inventorying and monitoring in Russia), Sovremennye problemy distantsionnogo zondirovaniya Zemli iz kosmosa, 2012, Vol. 9, No. 5, pp. 104-115.
- Savin I.Yu., Bartalev S.A., Loupian E.A., Tolpin V.A., Khvostikov S.A., Prognozirovanie urozhainosti selskokhoziaistvennyh kultur na osnove sputnikovyh dannyh: vozmozhnosti I perspektivy (Crop yield forecasting based on satellite data: possibilities and perspectives), Sovremennye problemy distantsionnogo zondirovaniya Zemli iz kosmosa, 2010, Vol. 7, No. 3, pp. 275-285.
- Tolpin V.A., Balashov I.V., Loupian E.A., Savin I.Yu., Sputnikovy servis “Vega” (Satellite service “Vega”), Zemlia iz Kosmosa, 2011, Release 9, spring, pp.32-37.
- Fomin N.P., Sapozhnikov P.M., Novye podhody k gosudarstvennoi kadastrovoi ozenke zemel selskohoziaystvennogo naznachenia [Data publikatsii – 20.10.2010] (New approaches to the state cadaster estimation of the earth of agricultural designation [date of publication - 20.10.2010]), http://www.valnet.ru/m7.phtml.
- Bala S.K., Islam A.S., Correlation between potato yield and MODIS-derived vegetation indices, International Journal of Remote Sensing, Vol. 30, Issue 10, January 2009, pp. 2491-2507.
- Baret F., Guyot G., Potentials and limits of vegetation indices for LAI and APAR assessment, Remote Sensing of Environment, 1991, 35:161-173.
- Benedetti R., Rossinni P., On the use of NDVI profiles as a tool for agricultural statistics: the case study of wheat yield estimate and forecast in Emilia Romagna, Remote Sensing of Environment, 1993, 45:311-326.
- Bouman B.A. M., Uenk D., Haverkort A.J. , Estimation of ground cover of potato by reflectance measurements, Potato Research, 1992, 35, 111-125.
- Elvidge C.D., Lyon R.J.P., Influence of rock-soil spectral variation on assessment of green biomass, Remote Sensing of Environment, 1985, 17:265-279.
- Huete A.R., Jackson R.D., Post D.F., Spectral response of a plant canopy with different soil backgrounds, Remote Sensing of Environment, 1985, 17:37-53.
- Groten S.M.E., NDVI crop monitoring and early yield assessment of Burkina Faso, International Journal of Remote Sensing, 1993, 14(8):1495-1515.
- Liu W.T., Kogan F., Monitoring Brazilian soybean production using NOAA/AVHRR based vegetation condition indices, International Journal of Remote Sensing, 2002, 23(6):1161-1179.
- Medvedeva M.A., Savin I.Yu., Isaev V.A., Determination of Area of Drought-Affected Crops Based on Satellite Data (Exemplified by Crops in Chuvashia in 2010), Russian Agricultural Sciences, 2012, Vol. 38, No. 2, pp.121-125.
- Quarmby N.A., Milnes M., Hindle T.L., Silicos N., The use of multitemporal NDVI measurements from AVHRR data for crop yield estimation and prediction, International Journal of Remote Sensing, 1993, 14:199-210.
- Rasmussen M.S., Operational Yield forecast using AVHRR NDVI data: reduction of environmental and inter-annual variability, International Journal of Remote Sensing, 1997, 18(5):1059-1077.
- Rembold F., Atzberger C., Savin I., Rojas O. Using low resolution satellite imagery for yield prediction and yield anomaly detection, Remote Sensing, 2013, Vol. 5, No. 4, pp. 1704-1733.
- Remote Sensing Support to Crop Yield Forecast and Area Estimates, The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences Vol. XXXVI, No. 8/W48 ISPRS WG VIII/10 Workshop 2006, Stresa, Italy.
- Saravanan S., Estimating Yield of Irrigated Potatoes Using Aerial and Satellite Remote Sensing. (2011), All Graduate Theses and Dissertations. Paper 1049.
- Savin I.Yu., Nègre T., Agro-meteorological Monitoring in Russia and Central Asian Countries - OPOCE EUR 22210EN, Ispra (Italy), 2006, 214p.
- Unganai L.S., Kogan F.N., Drought monitoring and Corn yield estimation in Southern Africa from AVHRR data, Remote Sensing of Environment, 1998, 63:219-232.
- Yang C., Everitt J.H., Bradford J.M., Escobar D.E., Mapping grain sorghum growth and yield variations using airborne multispectral digital imagery, Transactions of ASAE, 2000, 43(6):1927-1938.