The development of soil quality index in the vicinity of the Van Lake pasture lands located in the Northern East Part of Turkey under semi-arid terrestrial ecosystem is very important since there are certain degradation signs indicating how their sustainability is being threatened. A total of 150 soils in the pastures throughout the region were sampled and several soil physical, chemical and biological indicators were quantified. A minimum data set of the most sensitive indicators was chosen using principal component analyses. Linear scoring functions for these indicators were used to develop soil quality index integrated with remote sensing (RS) and geographical information system (GIS). In this current study, classes between SQIs calculated using the minimum data set (MDS) and total data set (TDS) approaches showed a parallel trend in each other and match analysis for agreement showed also a significant statistically relationship between TDS_SQI/MDS_SQI and REOSAVI in May and June months for pasture area. Furthermore, this study also showed that advance techniques (PCA, geostatistic, AHP-Fuzzy) and the technologies of RS and GIS, which are essential to the analysis and processing of original and generated information were used effectively by integrating each other for SQI in large area.

在半干旱陆地生态系统下位于土耳其东北部的范湖牧场附近的土壤质量指数的发展非常重要，因为存在一定程度的退化迹象表明它们的可持续性受到威胁。在整个地区的牧场中总共对150种土壤进行了采样，并对几种土壤物理，化学和生物学指标进行了定量。使用主成分分析选择了最敏感指标的最小数据集。这些指标的线性评分功能用于开发结合了遥感（RS）和地理信息系统（GIS）的土壤质量指数。在本研究中，_SQI / MDS _SQI和REOSAVI在5月和6月用于牧场。此外，这项研究还表明，通过相互集成大型SQI，有效地利用了对原始和生成的信息进行分析和处理所必需的先进技术（PCA，地统计学，AHP-Fuzzy）以及RS和GIS技术。区。