Multi-temporal analysis of land cover changes using Landsat data through Google Earth Engine platform

Author(s):  
Alessandra Capolupo ◽  
Cristina Monterisi ◽  
Mirko Saponaro ◽  
Eufemia Tarantino
Author(s):  
Emma Izquierdo-Verdiguier ◽  
Alvaro Moreno-Martinez ◽  
Jose E. Adsuara ◽  
Jordi Munoz-Mari ◽  
Gustau Camps-Valls ◽  
...  

2019 ◽  
Vol 11 (15) ◽  
pp. 1808 ◽  
Author(s):  
Zhou ◽  
Dong ◽  
Liu ◽  
Metternicht ◽  
Shen ◽  
...  

Unprecedented human-induced land cover changes happened in China after the Reform and Opening-up in 1978, matching with the era of Landsat satellite series. However, it is still unknown whether Landsat data can effectively support retrospective analysis of land cover changes in China over the past four decades. Here, for the first time, we conduct a systematic investigation on the availability of Landsat data in China, targeting its application for retrospective and continuous monitoring of land cover changes. The latter is significant to assess impact of land cover changes, and consequences of past land policy and management interventions. The total and valid observations (excluding clouds, cloud shadows, and terrain shadows) from Landsat 5/7/8 from 1984 to 2017 were quantified at pixel scale, based on the cloud computing platform Google Earth Engine (GEE). The results show higher intensity of Landsat observation in the northern part of China as compared to the southern part. The study provides an overall picture of Landsat observations suitable for satellite-based annual land cover monitoring over the entire country. We uncover that two sub-regions of China (i.e., Northeast China-Inner Mongolia-Northwest China, and North China Plain) have sufficient valid observations for retrospective analysis of land cover over 30 years (1987–2017) at an annual interval; whereas the Middle-Lower Yangtze Plain (MLYP) and Xinjiang (XJ) have sufficient observations for annual analyses for the periods 1989–2017 and 2004–2017, respectively. Retrospective analysis of land cover is possible only at a two-year time interval in South China (SC) for the years 1988–2017, Xinjiang (XJ) for the period 1992–2003, and the Tibetan Plateau (TP) during 2004–2017. For the latter geographic regions, land cover dynamics can be analyzed only at a three-year interval prior to 2004. Our retrospective analysis suggest that Landsat-based analysis of land cover dynamics at an annual interval for the whole country is not feasible; instead, national monitoring at two- or three-year intervals could be achievable. This study provides a preliminary assessment of data availability, targeting future continuous land cover monitoring in China; and the code is released to the public to facilitate similar data inventory in other regions of the world.


2017 ◽  
Vol 8 ◽  
pp. 278-290 ◽  
Author(s):  
Antonio J. Sanhouse-Garcia ◽  
Yaneth Bustos-Terrones ◽  
Jesús Gabriel Rangel-Peraza ◽  
Alberto Quevedo-Castro ◽  
Carlos Pacheco

2021 ◽  
Vol 10 (7) ◽  
pp. 464
Author(s):  
Jiansong Luo ◽  
Xinwen Ma ◽  
Qifeng Chu ◽  
Min Xie ◽  
Yujia Cao

Land use and land cover (LULC) are fundamental units of human activities. Therefore, it is of significance to accurately and in a timely manner obtain the LULC maps where dramatic LULC changes are undergoing. Since 2017 April, a new state-level area, Xiong’an New Area, was established in China. In order to better characterize the LULC changes in Xiong’an New Area, this study makes full use of the multi-temporal 10-m Sentinel-2 images, the cloud-computing Google Earth Engine (GEE) platform, and the powerful classification capability of random forest (RF) models to generate the continuous LULC maps from 2017 to 2020. To do so, a novel multiple RF-based classification framework is adopted by outputting the classification probability based on each monthly composite and aggregating the multiple probability maps to generate the final classification map. Based on the obtained LULC maps, this study analyzes the spatio-temporal changes of LULC types in the last four years and the different change patterns in three counties. Experimental results indicate that the derived LULC maps achieve high accuracy for each year, with the overall accuracy and Kappa values no less than 0.95. It is also found that the changed areas account for nearly 36%, and the dry farmland, impervious surface, and other land-cover types have changed dramatically and present varying change patterns in three counties, which might be caused by the latest planning of Xiong’an New Area. The obtained 10-m four-year LULC maps in this study are supposed to provide some valuable information on the monitoring and understanding of what kinds of LULC changes have taken place in Xiong’an New Area.


2010 ◽  
Vol 30 (4) ◽  
pp. 592-605 ◽  
Author(s):  
N. Bakr ◽  
D.C. Weindorf ◽  
M.H. Bahnassy ◽  
S.M. Marei ◽  
M.M. El-Badawi

Sign in / Sign up

Export Citation Format

Share Document