Monitoring Annual Land Use/Land Cover Change in the Tucson Metropolitan Area with Google Earth Engine (1986–2020)

Abstract

The Tucson metropolitan area, located in the Sonoran Desert of southeastern Arizona (USA), is affected by both massive population growth and rapid climate change, resulting in important land use and land cover (LULC) changes. As its fragile arid ecosystem and scarce resources are increasingly under pressure, there is a crucial need to monitor such landscape transformations. For such ends, we propose a method to compute yearly 30 m resolution LULC maps of the region from 1986 to 2020, using a combination of Landsat imagery, derived transformation and indices, texture analysis and other ancillary data fed to a Random Forest classifier. The entire process was hosted in the Google Earth Engine with tremendous computing capacities that allowed us to process a large amount of data and to achieve high overall classification accuracy for each year, ranging from 86.7 to 96.3%. Conservative post-processing techniques were also used to mitigate the persistent confusions between the numerous isolated houses in the region and their desert surroundings and to smooth year-specific LULC changes in order to identify general trends. We then show that policies to lessen urban sprawl in the area had little effects and we provide an automated tool to continue monitoring such dynamics in the future.

A Remote Sensing-Based Analysis of the Impact of Syrian Crisis on Agricultural Land Abandonment in Yarmouk River Basin

“…Meanwhile, they witnessed different changeable control authorities between the government, the opposition, and other local armed groups during 2011–2021. UNOCH [ 37 ] reported that before August 2018 the subsequent shifts in the security situation generated multiple repeated displacements as the internally displaced persons (IDPs) left their place of displacement to return home or fled again when hostilities resumed, or kept moving onwards as hostilities unfolded. After that, due to the apparent ceasing of armed conflict and the reconciliations with local tribes in southern and southwestern Syria, in addition to the stable authority of the Syrian government, many people tended to return to their towns and villages.…”

“…As a matter of fact, GEE is indeed a web-based open-source processing platform that combines a multi-petabyte catalog of satellite imagery and geospatial datasets with planetary-scale analysis capabilities. It uses Java scripts for downloading satellite data, detecting landscape changes, classifying land cover types, mapping trends, and quantifying differences on the Earth’s surface, and has been recently used for various remote sensing applications [ 36 , 37 ]. The dataset was collected from LANDSAT/LT05/C01/T1_SR and LANDSAT/LC08/C01/T1_SR for Landsat-5 and Landsat-8, respectively.…”

Temporal and Spatial Changes in Vegetation Ecological Quality and Driving Mechanism in Kökyar Project Area from 2000 to 2021

“…Third, we normalized the reflectance values using the nadir bidirectional reflectance distribution function (BRDF) correction to obtain seamless mosaics. In order to improve the classification accuracy, this study selected the NDVI, NDWI, NDBI, BAEI, NDBai, DBI, DBSI, and TPI as the characteristic variables of the random forest model (Table 2) [36]. Based on the surface characteristics of the study area, this study finally selected five land types, namely cropland, grassland, water, bare land, and built-up area.…”

The dynamics of land cover in conservation areas using cloud computing platform: Cases in Gunung Merbabu National Park

“…The use of GEE for land cover classification has been widely carried out with various satellite data sources, application locations, data analysis and use [35,36]. Land cover classification using GEE and time series has been carried out in several recent studies with the same objective of investigating land cover change and urban sprawl [37][38][39][40]. In this study, land cover classification is carried out in time series to see the dynamics of land cover changes in conservation areas in the GMbNP area and buffer area.…”