Detect geographic and temporal patterns of land use and land cover change in China from 1982 to 2012 Yaqian He, Eungul Lee, and Timothy A. Warner May 5 th, 2016 West Virginia GIS Conference
Contents Results Data & Methods Objectives Introduction
Geography of China (MODIS MCD12Q1: 2012) Introduction: Background Cropland Forest Grassland Barren
2013:1.37 billion people More food More water Introduction: Background
Desertification Agriculture Urbanization Deforestation Afforestation Introduction: Background
Introduction: Research gaps LULC map A potential vegetation map A map of a specific year representing the entire study period (Fu 2003; Zhu 2012)
Introduction: Research gaps LULC map A potential vegetation map A map of a specific year representing the entire study period Continuous annual land use and land cover map is needed to detect LULCC (Fu 2003; Zhu 2012)
Objectives Detect geographic and temporal patterns of land use and land cover change in China based on continuous annual LULC maps from 1982 to 2012
Data and Method: Data Datasets NOAA AVHRR GIMMS NDVI3g from 1982 to 2012 NASA MODIS MCD12Q1 from 2001 to 2012 Google Earth: land use and land cover images in 2012
1. Classification: Phenology Phenological metrics AVHRR GIMMS NDVI time- series from 1982 to 2012 Random Forests Annual LULC maps MODIS MCD12Q1 from 2001 to 2010 Geographic areas of unchanged land use and land cover Temporal filtering Data and Methods: Methods
2. Inter- comparison and Validation MODIS MCD12Q1, 300 samples from Google Earth LULC maps
Data and Methods: Methods 3. Change detection Annual LULC maps from 1982 to 2012 Geographic and temporal patterns of LULCC Linear regression trend analysis Y=a + bX + e
Results: LULC maps
Results: LULC maps Accuracy % for 2011, and 69.3% for 2012
Results: LULC maps Accuracy Overall accuracy 73.6% UMD 1992:69% GLC2000: 68.6% MODIS: 75% MERIS: 67.1% It is reliable to use our annual LULC maps!
Results: LULCC spatial pattern Cropland Forest Grassland
Results: LULCC temporal pattern
Thank you!