Mapping Soil Organic Matter in Black Soil Cropland Areas Using Remote Sensing and Environmental Covariates

Agriculture, Journal Year: 2025, Volume and Issue: 15(3), P. 339 - 339

Published: Feb. 4, 2025

The accurate prediction of soil organic matter (SOM) content is important for sustainable agriculture and effective management. This task particularly challenging due to the variability in factors influencing SOM distribution across different cultivated land types, as well site-specific responses remote sensing data environmental covariates, especially black region northeastern China, where exhibits significant spatial variability. study evaluated variations on importance imagery covariates zones. A total 180 samples (0–20 cm) were collected from Youyi County, Heilongjiang Province, multi-year synthetic bare images 2014 2022 (focusing April May) acquired using Google Earth Engine. Combining three types such drainage, climate topography, area was categorized into dry field paddy field. Then, model constructed random forest regression method accuracy strategies by 10-fold cross-validation. findings indicated that, (1) overall analysis, combining drainage variables May could attain highest accuracy, ranked follows: (RS) > (CLI) (DN) Topography (TP). (2) Zonal analysis conducted with a high degree precision, evidenced an R2 0.72 impressively low RMSE 0.73%. time window monitoring More specifically, optimal frames dryland identified May, while those fields concentrated May. (3) In addition, diverse observed vary types. regions characterized intricate fields, contributions assumed heightened importance. Conversely, featuring flat terrain, roles played more substantial role outcomes. These underscore selecting appropriate inputs improving accuracy.

Language: Английский

Hybrid GIS-MCDM Based Modeling Approach for Determination of Land Suitability of Wheat Cultivation in Konya Closed Basin, Türkiye

Tarım Bilimleri Dergisi, Journal Year: 2025, Volume and Issue: 31(2), P. 427 - 446

Published: March 25, 2025

In countries with high population growth and migration potential, such as Türkiye, agricultural lands are gradually decreasing due to the increase in food demand misusage policies urbanization applied lands. Land suitability activities carried out within scope of sustainability order production soil productivity important. This study focuses on identifying suitable for wheat cultivation by evaluating Konya closed basin Central Anatolia Region Türkiye using a hierarchy developed integration AHP method, which is one GIS MCDM techniques. Within this framework, 15 criteria were delineated under 4 main headings meteorological criteria, topographic infrastructure economic their weight values sub-criteria calculated. The most effective determined average temperature October (0.1379), followed annual (0.1300) land use capability (0.1191). Finally, map was created cultivation. According map, 0.39% (15 815 km2) area found be very highly cultivation, 61.24% (2 494 461 terms suitability. districts Kadinhani, Sarayonu, Altinekin, Cihanbeyli, Kulu, Karapinar Emirgazi, located north area, have been regions aims contribute existing literature precise areas combining site selection process. study, new research perspective presented taking into account uncertainty process concept four different dimensions: meteorological, topographical, soil, economic, thus aiming guide decision-makers future studies. current literature, that no comprehensive has yet conducted covers large plant, raw material humanity's basic nutritional needs. addition, pressure criterion not examined discussed its importance plant development also examined. Consequently, outcome delineates methods used may guiding studies covering wide areas.

Language: Английский

Evaluating UAV Alternatives for Post-Disaster Situations: An Integrated Decision-Making Methodology

IEEE Access, Journal Year: 2024, Volume and Issue: 12, P. 183489 - 183509

Published: Jan. 1, 2024

Language: Английский