A Novel Spatial Simulation Method for Mapping the Urban Forest Carbon Density in Southern China by the Google Earth Engine

Autor:	Mykola Kutia, Chuanshi Chen, Fugen Jiang, Hua Sun, Chengjie Li
Rok vydání:	2021
Předmět:	Landsat 8 Coefficient of determination 010504 meteorology & atmospheric sciences Mean squared error forest carbon density Science geographically weighted regression Global warming 0211 other engineering and technologies 02 engineering and technology Spatial distribution 01 natural sciences Random forest GEE Urban forest Linear regression General Earth and Planetary Sciences Environmental science Terrestrial ecosystem Physical geography 021101 geological & geomatics engineering 0105 earth and related environmental sciences
Zdroj:	Remote Sensing; Volume 13; Issue 14; Pages: 2792 Remote Sensing, Vol 13, Iss 2792, p 2792 (2021)
ISSN:	2072-4292
DOI:	10.3390/rs13142792
Popis:	Urban forest is an important component of terrestrial ecosystems and is highly related to global climate change. However, because of complex city landscapes, deriving the spatial distribution of urban forest carbon density and conducting accuracy assessments are difficult. This study proposes a novel spatial simulation method, optimized geographically weighted logarithm regression (OGWLR), using Landsat 8 data acquired by the Google Earth Engine (GEE) and field survey data to map the forest carbon density of Shenzhen city in southern China. To verify the effectiveness of the novel method, multiple linear regression (MLR), k-nearest neighbors (kNN), random forest (RF) and geographically weighted regression (GWR) models were established for comparison. The results showed that OGWLR achieved the highest coefficient of determination (R2 = 0.54) and the lowest root mean square error (RMSE = 13.28 Mg/ha) among all estimation models. In addition, OGWLR achieved a more consistent spatial distribution of carbon density with the actual situation. The carbon density of the forests in the study area was large in the central and western regions and coastal areas and small in the building and road areas. Therefore, this method can provide a new reference for urban forest carbon density estimation and mapping.
Databáze:	OpenAIRE
Externí odkaz:	https://explore.openaire.eu/search/publication?articleId=doi_dedup___::3b58a1b7fa8b3ffaf4de8c4a20929beb https://doi.org/10.3390/rs13142792 Zobrazit plný text záznamu Plný text ve formátu PDF Plný text ve formátu HTML
Nepřihlášeným uživatelům se plný text nezobrazuje	K zobrazení výsledku je třeba se přihlásit.