remote sensing Article Detecting Ecological Changes with a Remote Sensing Based Ecological Index (RSEI) Produced Time Series and Change Vector Analysis Hanqiu Xu 1,* , Yifan Wang 1, Huade Guan 2, Tingting Shi 1 and Xisheng Hu 1,3 1 College of Environment and Resources, Key Laboratory of Spatial Data Mining & Information Sharing of Ministry of Education, Institute of Remote Sensing Information Engineering, Fujian Provincial Key Laboratory of Remote Sensing of Soil Erosion, Fuzhou University, Fuzhou 350116, China;
[email protected] (Y.W.);
[email protected] (T.S.);
[email protected] (X.H.) 2 National Centre for Groundwater Research and Training, College of Science and Engineering, Flinders University, Adelaide, SA 5001, Australia; huade.guan@flinders.edu.au 3 College of Transportation and Civil Engineering, Fujian Agriculture and Forestry University, Fuzhou 350002, China * Correspondence:
[email protected]; Tel.: +86-591-2286-6071 Received: 20 August 2019; Accepted: 8 October 2019; Published: 10 October 2019 Abstract: Increasing human activities have caused significant global ecosystem disturbances at various scales. There is an increasing need for effective techniques to quantify and detect ecological changes. Remote sensing can serve as a measurement surrogate of spatial changes in ecological conditions. This study has improved a newly-proposed remote sensing based ecological index (RSEI) with a sharpened land surface temperature image and then used the improved index to produce the time series of ecological-status images. The Mann–Kendall test and Theil–Sen estimator were employed to evaluate the significance of the trend of the RSEI time series and the direction of change. The change vector analysis (CVA) was employed to detect ecological changes based on the image series.