Using Remote Sensing to Map and Monitor Fire Damage in Forest Ecosystems

2006 ◽  
pp. 127-146
Keyword(s):  
Remote Sensing ◽  
Forest Ecosystems ◽  
Fire Damage

scholarly journals Using remote sensing to assess tsunami-induced impacts on coastal forest ecosystems at the Andaman Sea coast of Thailand

2010 ◽  
Vol 10 (4) ◽  
pp. 729-745 ◽  
Author(s):  
H. Roemer ◽  
G. Kaiser ◽  
H. Sterr ◽  
R. Ludwig
Keyword(s):  
Remote Sensing ◽  
Forest Ecosystems ◽  
Ground Truth ◽  
Andaman Sea ◽  
Coastal Forest ◽  
Coastal Forests ◽  
Change Detection Algorithms ◽  
Damage Maps ◽  
2004 Tsunami ◽  
Sea Coast

Abstract. The December 2004 tsunami strongly impacted coastal ecosystems along the Andaman Sea coast of Thailand. In this paper tsunami-induced damage of five different coastal forest ecosystems at the Phang-Nga province coast is analysed with a remote sensing driven approach based on multi-date IKONOS imagery. Two change detection algorithms, change vector analysis (CVA) and direct multi-date classification (DMC), are applied and compared regarding their applicability to assess tsunami impacts. The analysis shows that DMC outperforms CVA in terms of accuracy (Kappa values for DMC ranging between 0.947 and 0.950 and between 0.610–0.730 for CVA respectively) and the degree of detail of the created change classes. Results from DMC show that mangroves were the worst damaged among the five forests, with a 55% of directly damaged forest in the study area, followed by casuarina forest and coconut plantation. Additionally this study points out the uncertainties in both methods which are mainly due to a lack of ground truth information for the time between the two acquisition dates of satellite images. The created damage maps help to better understand the way the tsunami impacted coastal forests and give basic information for estimating tsunami sensitivity of coastal forests.

scholarly journals Remote sensing and ecosystem modeling to simulate terrestrial carbon fluxes

2019 ◽  
pp. 87
Author(s):  
Sergio Sánchez-Ruiz
Keyword(s):  
Remote Sensing ◽  
Carbon Cycle ◽  
Spatial Scale ◽  
Forest Ecosystems ◽  
Carbon Fluxes ◽  
Daily Basis ◽  
Ecosystem Models ◽  
Validation Process ◽  
Data Source ◽  
Peninsular Spain

<p>The main goal of this thesis is the establishment of a framework to analyze the forest ecosystems in peninsular Spain in terms of their role in the carbon cycle. In particular, the carbon fluxes that they exchange with atmosphere are modeled to evaluate their potential as carbon sinks and biomass reservoirs. The assessment of gross and net carbon fluxes is performed at 1-km spatial scale and on a daily basis using two different ecosystem models, Monteith and BIOME-BGC, respectively. These models are driven by a combination of satellite and ground data, part of the latter being also employed as a complementary data source and in the validation process.</p>

scholarly journals AEROSPACE MONITORING OF THE FOREST ECOSYSTEM DYNAMICS WITHIN THE TERRITORY OF VRACHANSKI BALKAN NATURE PARK

2018 ◽  
pp. 41-46
Author(s):  
Adlin Dancheva
Keyword(s):  
Remote Sensing ◽  
Forest Ecosystem ◽  
Vegetation Index ◽  
Forest Ecosystems ◽  
Normalized Difference Vegetation Index ◽  
Remote Sensing And Gis ◽  
Ecosystem Dynamics ◽  
Anthropogenic Pressure ◽  
Water Index ◽  
Nature Park

In this paper the application of Remote Sensing and GIS as a means of performing aero – space monitoring of forest ecosystems dynamics is being considered. The purpose of this work is to create a model for monitoring the dynamic of forest ecosystems, based on Remote Sensing and GIS. The results of eco-monitoring can be used to update plans and policies for forest ecosystem management. The territory of Vrachanski Balkan Nature park was chosen as the subject of research as there is a certain anthropogenic pressure there. The results presented are obtained by spatial-time analysis of certain aerospace data indices. To carry out the study optical satellite images were used, on the basics of which three indices were calculated: Normalized Difference Vegetation Index (NDVI), Normalized Difference Water Index (NDWI) and Normalized Difference Greenness Index (NDGI). A comparative analysis has been created and results of the degree of correlation between the different indices are presented, as well as indicators from the different test areas and related changes in the individual points in time. The results of the survey aim to assess the dynamics and condition of the forest vegetation on the territory of Vrachanski Balkan Nature park and can be utilised in activities related to monitoring, mapping and forest management.

A survey of remote sensing-based aboveground biomass estimation methods in forest ecosystems

2014 ◽  
Vol 9 (1) ◽  
pp. 63-105 ◽  
Author(s):  
Dengsheng Lu ◽  
Qi Chen ◽  
Guangxing Wang ◽  
Lijuan Liu ◽  
Guiying Li ◽  
...  
Keyword(s):  
Remote Sensing ◽  
Aboveground Biomass ◽  
Forest Ecosystems ◽  
Estimation Methods ◽  
Biomass Estimation

Hyperspectral remote sensing for estimating biophysical parameters of forest ecosystems

1999 ◽  
Vol 23 (3) ◽  
pp. 359-390 ◽  
Author(s):  
Paul M. Treitz ◽  
Philip J. Howarth
Keyword(s):  
Remote Sensing ◽  
Ecosystem Health ◽  
Forest Ecosystems ◽  
Structural Features ◽  
Biophysical Parameters ◽  
Physiological Character ◽  
Forest Condition ◽  
Hyperspectral Sensors ◽  
Physiological Information ◽  
The Relationship

Remote sensing has demonstrated wide applicability in the area of estimating and mapping forest physical and structural features. Focus in recent years has been directed towards measuring the biophysical/physiological character of forest ecosystems in order to estimate and predict forest ecosystem health and sustainability. The following reviews the relationship between forest condition and reflectance; remote-sensing measurements (and derivatives) that provide biophysical/physiological information; and the potential of hyperspectral sensors in the measurement of these parameters.

scholarly journals Applying geostatistics for investigations of forest ecosystems using remote sensing imagery

Silva Fennica ◽  
2005 ◽  
Vol 39 (4) ◽  
Author(s):  
Jaroslaw Zawadzki ◽  
Chris Cieszewski ◽  
Michal Zasada ◽  
Roger Lowe
Keyword(s):  
Remote Sensing ◽  
Forest Ecosystems ◽  
Remote Sensing Imagery

LiDAR remote sensing of forest structure

2003 ◽  
Vol 27 (1) ◽  
pp. 88-106 ◽  
Author(s):  
Kevin Lim ◽  
Paul Treitz ◽  
Michael Wulder ◽  
Benoît St-Onge ◽  
Martin Flood
Keyword(s):  
Remote Sensing ◽  
Forest Structure ◽  
Forest Ecosystems ◽  
Canopy Height ◽  
Forest Monitoring ◽  
Light Detection And Ranging ◽  
Lidar Data ◽  
Above Ground Biomass ◽  
Ground Biomass ◽  
Canopy Volume

Light detection and ranging (LiDAR) technology provides horizontal and vertical information at high spatial resolutions and vertical accuracies. Forest attributes such as canopy height can be directly retrieved from LiDAR data. Direct retrieval of canopy height provides opportunities to model above-ground biomass and canopy volume. Access to the vertical nature of forest ecosystems also offers new opportunities for enhanced forest monitoring, management and planning.

scholarly journals Crossing the Great Divide: Bridging the Researcher–Practitioner Gap to Maximize the Utility of Remote Sensing for Invasive Species Monitoring and Management

2021 ◽  
Vol 13 (20) ◽  
pp. 4142
Author(s):  
Kelsey Parker ◽  
Arthur Elmes ◽  
Peter Boucher ◽  
Richard A. Hallett ◽  
John E. Thompson ◽  
...  
Keyword(s):  
Remote Sensing ◽  
Invasive Species ◽  
Forest Ecosystems ◽  
Forest Health ◽  
Hemlock Woolly Adelgid ◽  
Adelges Tsugae ◽  
Forest Pest ◽  
Field Surveys ◽  
Health Decline ◽  
Symbiotic Mutualism

Invasive species are increasingly present in our ecosystems and pose a threat to the health of forest ecosystems. Practitioners are tasked with locating these invasive species and finding ways to mitigate their spread and impacts, often through costly field surveys. Meanwhile, researchers are developing remote sensing products to detect the changes in vegetation health and structure that are caused by invasive species, which could aid in early detection and monitoring efforts. Although both groups are working towards similar goals and field data are essential for validating RS products, these groups often work independently. In this paper, we, a group of researchers and practitioners, discuss the challenges to bridging the gap between researchers and practitioners and summarize the literature on this topic. We also draw from our experiences collaborating with each other to advance detection, monitoring, and management of the Hemlock Woolly Adelgid (Adelges tsugae; HWA), an invasive forest pest in the eastern U.S. We conclude by (1) highlighting the synergies and symbiotic mutualism of researcher–practitioner collaborations and (2) providing a framework for facilitating researcher–practitioner collaborations that advance fundamental science while maximizing the capacity of RS technologies in monitoring and management of complex drivers of forest health decline such as invasive species.

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