Standardized minNDTI index as a criterion for identifying farms using no-till
The experience of selecting data for constructing a minNDTI sample to identify farms using no-till in two agroecological zones of the Stavropol Territory with different agro-climatic conditions is presented. Due to the annual increase in the areas occupied by conservation technologies (in particular no-till), the development of systems for allocation and accounting is an urgent task for science and industry. The crop residues preserved during no-till create characteristic surface properties that can be used to isolate such farms based on remote sensing data. A common approach to identify farms using no-till (PP) is the use of the NDTI spectral index and its multitemporal derivative, minNDTI. As part of the study, collections of standardized minNDTI data for each year from 2019 to 2023 were selected, characterizing no-till and traditional technology for two agroclimatic zones: an unstable humidification and an arid. The possibility of using the threshold values of the NDVI vegetation index to clear samples from data corresponding to living vegetation, the possibility of using two time ranges to build the minNDTI dataset, the possibility of using Landsat and Sentinel-2 data was analyzed. The total number of analyzed samples – 16. The optimal threshold for excluding living vegetation from the minNDTI samples is 0.3. At NDVI 0.2, significant data loss occurs. The standardized minNDTI data obtained for the arid zone of the Stavropol Territory are typical for each year of the study, which gives reason to believe that it is possible to use the presented data to identify farms using no-till for any time period. The use of the minNDTI index to identify farms using no-til is optimal for regions with agro-climatic conditions similar to the Arid zone of the Stavropol Territory.
Authors
- Viktor Belobrov
- V. K. Dridiger (ORCID: https://orcid.org/0000-0002-0510-2220)
- S. G. Yudin
- I. A. Nadutkin (ORCID: https://orcid.org/0009-0002-7931-352X)
- Dmitry Shapovalov
- Rasul Gadzhiumarov
- Nikita Ermolaev
Institutions
- State University of Land Use Planning (RU)
- V.V. Dokuchaev Soil Science Institute (RU)
Publication Details
- Journal
- Mezhdunarodnyi sel skokhozyaistvennyi zhurnal
- Published
- 2024-08-15
- DOI
- https://doi.org/10.55186/25876740_2024_67_4_487
- Primary Topic
- Remote Sensing in Agriculture
- Type
- article
- Field-Weighted Citation Impact
- 0.00