Mapping Soil Salinity/Sodicity by using Landsat OLI Imagery and PLSR Algorithm over Semiarid West Jilin Province, China
| Autor: | Bai Zhang, Liangjun Hu, Mingyue Liu, Baojia Du, Zongming Wang, Hao Yu |
|---|---|
| Jazyk: | angličtina |
| Rok vydání: | 2018 |
| Předmět: |
soil salinity
Soil salinity 010504 meteorology & atmospheric sciences hybridized salinity and sodicity (HSS) Soil science Land cover lcsh:Chemical technology Spatial distribution 01 natural sciences Biochemistry Article Analytical Chemistry lcsh:TP1-1185 Electrical and Electronic Engineering Instrumentation Land resources Landsat 8 OLI 0105 earth and related environmental sciences soil sodicity Partial Least Square Regression (PLSR) Soil classification 04 agricultural and veterinary sciences Reflectivity Atomic and Molecular Physics and Optics Salinity Soil water 040103 agronomy & agriculture 0401 agriculture forestry and fisheries Environmental science |
| Zdroj: | Sensors (Basel, Switzerland) Sensors; Volume 18; Issue 4; Pages: 1048 Sensors, Vol 18, Iss 4, p 1048 (2018) |
| ISSN: | 1424-8220 |
| Popis: | Soil salinity and sodicity can significantly reduce the value and the productivity of affected lands, posing degradation, and threats to sustainable development of natural resources on earth. This research attempted to map soil salinity/sodicity via disentangling the relationships between Landsat 8 Operational Land Imager (OLI) imagery and in-situ measurements (EC, pH) over the west Jilin of China. We established the retrieval models for soil salinity and sodicity using Partial Least Square Regression (PLSR). Spatial distribution of the soils that were subjected to hybridized salinity and sodicity (HSS) was obtained by overlay analysis using maps of soil salinity and sodicity in geographical information system (GIS) environment. We analyzed the severity and occurring sizes of soil salinity, sodicity, and HSS with regard to specified soil types and land cover. Results indicated that the models’ accuracy was improved by combining the reflectance bands and spectral indices that were mathematically transformed. Therefore, our results stipulated that the OLI imagery and PLSR method applied to mapping soil salinity and sodicity in the region. The mapping results revealed that the areas of soil salinity, sodicity, and HSS were 1.61 × 106 hm2, 1.46 × 106 hm2, and 1.36 × 106 hm2, respectively. Also, the occurring area of moderate and intensive sodicity was larger than that of salinity. This research may underpin efficiently mapping regional salinity/sodicity occurrences, understanding the linkages between spectral reflectance and ground measurements of soil salinity and sodicity, and provide tools for soil salinity monitoring and the sustainable utilization of land resources. |
| Databáze: | OpenAIRE |
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