NDLI: Response of the regression tree model to high resolution remote sensing data for predicting percent tree cover in a Mediterranean ecosystem

Content Provider	Springer Nature Link
Author	Donmez, Cenk Berberoglu, Suha Erdogan, Mehmet Akif Tanriover, Anil Akin Cilek, Ahmet
Copyright Year	2015
Abstract	Percent tree cover is the percentage of the ground surface area covered by a vertical projection of the outermost perimeter of the plants. It is an important indicator to reveal the condition of forest systems and has a significant importance for ecosystem models as a main input. The aim of this study is to estimate the percent tree cover of various forest stands in a Mediterranean environment based on an empirical relationship between tree coverage and remotely sensed data in Goksu Watershed located at the Eastern Mediterranean coast of Turkey. A regression tree algorithm was used to simulate spatial fractions of Pinus nigra, Cedrus libani, Pinus brutia, Juniperus excelsa and Quercus cerris using multi-temporal LANDSAT TM/ETM data as predictor variables and land cover information. Two scenes of high resolution GeoEye-1 images were employed for training and testing the model. The predictor variables were incorporated in addition to biophysical variables estimated from the LANDSAT TM/ETM data. Additionally, normalised difference vegetation index (NDVI) was incorporated to LANDSAT TM/ETM band settings as a biophysical variable. Stepwise linear regression (SLR) was applied for selecting the relevant bands to employ in regression tree process. SLR-selected variables produced accurate results in the model with a high correlation coefficient of 0.80. The output values ranged from 0 to 100 %. The different tree species were mapped in 30 m resolution in respect to elevation. Percent tree cover map as a final output was derived using LANDSAT TM/ETM image over Goksu Watershed and the biophysical variables. The results were tested using high spatial resolution GeoEye-1 images. Thus, the combination of the RT algorithm and higher resolution data for percent tree cover mapping were tested and examined in a complex Mediterranean environment.
Starting Page	1
Ending Page	12
Page Count	12
File Format	PDF
ISSN	01676369
Journal	Environmental Monitoring and Assessment
Volume Number	187
Issue Number	2
e-ISSN	15732959
Language	English
Publisher	Springer International Publishing
Publisher Date	2015-01-22
Publisher Place	Cham
Access Restriction	One Nation One Subscription (ONOS)
Subject Keyword	Remote sensing Percent tree cover Landsat Regression tree model Goksu watershed Environmental Monitoring/Analysis Environmental Management Ecotoxicology Atmospheric Protection/Air Quality Control/Air Pollution Ecology
Content Type	Text
Resource Type	Article
Subject	Pollution Medicine Management, Monitoring, Policy and Law

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