Identification of Successional Stages and Cover Changes of Tropical Forest Based on Digital Surface Model Analysis

Abstract

Forests are in a permanent state of change due to natural and anthropogenic processes. Long-term time series analysis makes it possible to reconstruct the forest history and perform a multitemporal analysis on the cause and effect of changes. This paper describes an approach for successional stage classification in a tropical forest based on vertical structure variations. Stereophotogrammetry and novel image matching methods are used to produce dense digital surface models (DSMs) from optical images (historical and contemporary). An approach was developed to classify the successional stages of trees using local height variations provided by a DSM and image intensity values. Experiments were performed in a semi-deciduous tropical forest fragment located in the West of São Paulo State, Brazil. Six test sample plots and a line transect were established and field surveys were conducted to collect forest variables. These variables were used to characterize and validate five successional classes based on secondary tree species that stratify the forest canopy. The current status of the entire forest fragment was characterized using recent photogrammetric imagery, and a map of historical successional stages was established by analyzing the historical photogrammetric imagery. The investigation demonstrated that the proposed technique can be used to reconstruct the geometric structure of a forest canopy from aerial images. The successional stages can be identified and compared over time using multitemporal photogrammetric imagery and DSMs, which enables an analysis of forest cover changes. The results indicated that the successional stage has changed dramatically during the 50 years period of time.

Uav-Based Photogrammetric Point Clouds and Hyperspectral Imaging for Mapping Biodiversity Indicators in Boreal Forests

“…However, the mean error for Hst.dev of 0.5 m is similar or better compared to results of other studies using UAV-based photogrammetric point clouds in estimating tree height (Zarco-Tejada et al 2014, Zahawi et al 2015, Wallace et al 2016. Berveglieri et al (2016) used photogrammetric point clouds to derive information from vertical structure of Brazilian semideciduous tropical forest and concluded that it was possible to classify successional stage with this information. Based on also our results, the accuracy of height variation could be used for estimating biodiversity when assessed with vertical structure of a forest.…”

Assessment of Various Remote Sensing Technologies in Biomass and Nitrogen Content Estimation Using an Agricultural Test Field

“…A professional drone (hexacopter with Tarot 960 foldable frame) equipped with a hyperspectral camera based on Fabry-Pérot interferometer (UAV FPI) and a good quality Samsung NX500 RGB camera (UAV RGB) were used. Different versions of this light-weight FPI hyperspectral camera (Saari et al, 2011;Oliveira et al, 2016a) have showed potential in both agriculture Kaivosoja et al, 2013) and other vegetation mapping tasks (Näsi et al, 2015;Berveglieri et al, 2016;Moriya et al, 2017;Nevalainen et al, 2017). In this study, FPI2012b sensor was configured with 36 spectral bands in 500 nm to 900 nm spectral range.…”

Assessing Biodiversity in Boreal Forests with UAV-Based Photogrammetric Point Clouds and Hyperspectral Imaging

“…Photogrammetric point clouds were used to derive information from vertical structure of Brazilian semideciduous tropical forest in [74], and they concluded that it was possible to classify successional stage with this information. Our results support their findings.…”