Modeling of Forest Communities’ Spatial Structure at the Regional Level through Remote Sensing and Field Sampling: Constraints and Solutions
This study tests modern approaches to spatial modeling of forest communities at the regional level based on a supervised classification. The study is conducted by the example of mapping the composition of forest communities in a large urbanized region (the Moscow Region, area 4.69 million hectares)....
Main Authors: | Ivan Kotlov, Tatiana Chernenkova |
---|---|
Format: | Article |
Language: | English |
Published: |
MDPI AG
2020-10-01
|
Series: | Forests |
Subjects: | |
Online Access: | https://www.mdpi.com/1999-4907/11/10/1088 |
Similar Items
-
Role of Silviculture in the Formation of Norway Spruce Forests along the Southern Edge of Their Range in the Central Russian Plain
by: Tatiana Chernenkova, et al.
Published: (2020-07-01) -
Epidemiology and spatial distribution of bluetongue virus in Xinjiang, China
by: Jun Ma, et al.
Published: (2019-02-01) -
Altitudinal shifting of major forest tree species in Italian mountains under climate change
by: Sergio Noce, et al.
Published: (2023-09-01) -
Application of a niche-based model for forest cover classification
by: Amici V, et al.
Published: (2012-05-01) -
A Comparison of Two Machine Learning Classification Methods for Remote Sensing Predictive Modeling of the Forest Fire in the North-Eastern Siberia
by: Piotr Janiec, et al.
Published: (2020-12-01)