Identifying the changes and relationships between regional eco-environment quality and landscape pattern in an urban agglomeration have a great significance in realizing sustainable development goal. However, limited research has been performed to understand the spatiotemporal change of ecoenvironment quality, the variation of landscape pattern, and their relationship in an urban agglomeration. This study selected the Jing-Jin-Ji (JJJ) urban agglomeration as the study area. A comprehensive index, the remote sensing ecological index (RSEI), was utilized to understand the eco-environment spatiotemporal change and landscape pattern variation at class-level and landscape-level of JJJ during 2001~2015, then, their relationship was explored. The major conclusions were as follows: (1) The average RSEI value of JJJ increased from 0.43 to 0.46, which represented that the eco-environment of JJJ had improved in the fourteen years. Among it, the improved region was mainly located in Zhangjiakou city, while the degraded region was mainly distributed in the eastern Hebei plain. (2) The landscape characteristics of entire JJJ ecoenvironment were becoming more aggregated, connected, diverse, and regular. However, fair, moderate, and good grades were getting more concentrated and continuous; poor grade indicated a more fragmented and disconnected trend; excellent grade displayed an expanded and concentrated situation. (3) Human factors have an increasing influence on regional eco-environment changes. (4) Fair, moderate, and good grades showed a more dominant and stronger influence on the variation of landscape pattern in JJJ. Specifically, the fair grade had a positive correlation with the variation of landscape pattern, while moderate and good grades had a negative one. All of these conclusions could be valuable information for relevant decision-makers in managing or achieving the optimal eco-environment landscape pattern. INDEX TERMS Jing-Jin-Ji urban agglomeration, landscape pattern, remote sensing ecological index, spatiotemporal change.

Exploring the regional eco-environmental quality (EEQ) and its driving factors is of great significance for regional management. Although existing studies have paid much attention to evaluate EEQ, few studies have been performed to investigate the spatiotemporal variations of EEQ and its driving factors in different ecosystem service regions (ESR) at an urban agglomeration scale. In this study, we selected Jing-Jin-Ji urban agglomeration (JJJ) as the study area to evaluate its EEQ, analyze its spatiotemporal variations, and investigate potential driving factors explanatory power based on the geographical detector methods in different ESR during 2001~2015. The main conclusions were as follows: (1) The EEQ of JJJ had improved from 2001 to 2015, with the average RSEI increased from 0.43 to 0.46; among them, Bashang Plateau and Western Hebei Ecosystem Service Region (BWHE) had the highest RSEI change rate (+26.19%) and the highest NTEDI value (0.13), while Central Hebei Plain Ecosystem Service Region (CHPE) had the lowest RSEI change rate (-5.41%) and the lowest NTEDI value (-0.02). (2) The EEQ of JJJ had strong spatial agglomeration effects, with the global Moran's I increased from 0.82 to 0.88. Spatially, the LL regions mainly changed into the HH regions in the northwestern part, while in the central and eastern areas, some isolated LL regions displayed an aggregated trend. (3) In terms of the driving factors, soil type and elevation were primary factors in explaining the variations of EEQ. Specifically, natural factors explained the highest variations in BWHE. The interaction of topographical and socio-economic factors had high explanatory power in Yanshan and Taihang Mountain Ecosystem Service Region (YTME) and CHPE; To Bohai and Coastal Ring Ecosystem Service Region (BCRE), the interaction of meteorological and socio-economic factors accounted for the high variations of EEQ. All these findings could provide more valuable advice for relevant policy-makers.INDEX TERMS Eco-environmental quality, remote sensing ecological index, Jing-Jin-Ji, Geographical detector, ecosystem service region.