Abstract: With the support of remote sensing(RS)and geographical information system(GIS)techniques, we present an integrated approach of remote sensing classification, connectivity metrics analysis and least-cost path simulation to develop urban potential green corridors in urban greenspace system planning. Firstly, this paper used the OIF(optimal index factor)and decision tree algorithms (QUEST)to extract urban greenspace patches, and analyzed the connectivity of each patch. Then, Spearman rank correlation coefficient was derived to determine the connectivity metrics sensitivity due to distance changes. Based on this, the most robust connectivity index was determined to divide patches importance rank, the patches with higher importance values were defined as greenspace ‘sources’ and ‘target’. Ultimately, the potential green corridors were simulated by using the least-cost model based on FR(frequency ratio)cost-surface under different research scales, followed by a quantitative evaluation of different scenarios simulation results. The preliminary results were as follows: 1)The total classification accuracy reached 90.35% by using OIF and QUEST, with a Kappa coefficient of 0.86; greenspace mainly distributed in the east of Gehu Lake and in the north of Taihu Lake, and accounted for 22.88% of the total area. 2)Integral index of connectivity(IIC)had higher robust with lower difference value of r_s(0.21)between 200 and 2 400 m distance threshold; under the 600 m threshold distance, the Zhushan patch and other seven patches were identified as ‘sources’ and ‘target’ by comparing important values(dIIC above 1%). 3)The spatial patterns of potential green corridors were hardly affected by research scales changes, with stable deformation coefficient(1.28). Finally, we discussed the feasibility of the optimized method system, and provided scientific and reasonable references for the planning and construction of city green system.

Key words: decision tree classification, optimization of connectivity metrics, improved cost-surface, multi-scale, potential green corridors, Changzhou