Modeling salinized wasteland using remote sensing with the integration of decision tree and multiple validation approaches in Hetao irrigation district of China

Abstract The salinized wasteland (SW) is a buffer zone to accumulate salt introduced from irrigation water in salinized irrigation districts. It is crucial to identify the locations and sizes of SW to achieve effective land management and reclamation, as well as agricultural sustainable development. However, the SW is less explored due to the lack of low-cost and effective techniques. In this study, a decision tree-based remote sensing model was proposed to distinguished SW from other land types using the high-resolution Gaofen-1 (GF-1) images in the Hetao Irrigation District of China during 2017–2020. Meanwhile, multiple validation approaches including points (field and random points) and area (small and medium-sized SWs, i.e., SWA, SWB) matching validations were adopted. To establish the model of SW, four spectral indices including Normalized Difference Vegetation Index (NDVI), Enhanced Vegetation Index (EVI), Normalized Difference Water Index (NDWI), and Salinity Index (SI), as well as a series of multi-period and multi-year remote sensing images were used. The threshold values of the four spectral indices were determined based on the probability density curve. The SW remote sensing model was highly accurate and reliable. The average producer accuracy (PA) and average user accuracy (UA) were respectively 88.0% and 81.6% for field investigation (field points matching validation), and 85.9% and 80.1% for Google Earth image investigation (random points matching validation). Besides, the average overlapping rate and misclassification rate were respectively 95.6% and 2.3% for small-sized typical SWs (area validation), and 92.9% and 4.7% for medium-sized typical SWs during 2017–2020. The model indicated that the SW area in the region was respectively 9969, 9694, 9660, and 9608 ha from 2017 to 2020. The area of small and medium-sized SWs decreased with time, while that of large-sized SWs was the opposite.