Monitoring of Vegetation Disturbance around Protected Areas in Central Tanzania Using Landsat Time-Series Data

Understanding vegetation disturbance around protected areas (PAs) is critical as it significantly affects the sustainable conservation of wildlife. However, there is a lack of analyses of consistent long-term data on vegetation disturbance. In this study, the LandTrendr algorithm and Google Earth En...

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Main Authors: Atupelye W. Komba, Teiji Watanabe, Masami Kaneko, Mohan Bahadur Chand
Format: Article
Language:English
Published: MDPI AG 2021-05-01
Series:Remote Sensing
Subjects:
Online Access:https://www.mdpi.com/2072-4292/13/9/1800
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spelling doaj-0d78fe46e6f24a1faff14b40d2f6a3022021-05-31T23:16:14ZengMDPI AGRemote Sensing2072-42922021-05-01131800180010.3390/rs13091800Monitoring of Vegetation Disturbance around Protected Areas in Central Tanzania Using Landsat Time-Series DataAtupelye W. Komba0Teiji Watanabe1Masami Kaneko2Mohan Bahadur Chand3Graduate School of Environmental Science, Hokkaido University, Sapporo 060-0810, JapanFaculty of Environmental Earth Science, Hokkaido University, Sapporo 060-0810, JapanCollege of Agriculture, Food and Environment Sciences, Rakuno Gakuen University, Ebetsu 069-8501, JapanFaculty of Environmental Earth Science, Hokkaido University, Sapporo 060-0810, JapanUnderstanding vegetation disturbance around protected areas (PAs) is critical as it significantly affects the sustainable conservation of wildlife. However, there is a lack of analyses of consistent long-term data on vegetation disturbance. In this study, the LandTrendr algorithm and Google Earth Engine were used to access satellite data and explore the vegetation dynamics history across the Ruaha–Rungwa landscape, Tanzania. We characterized vegetation disturbance patterns and change attributes, including disturbance occurrence trends, rate, and severity, by using each pixel’s normalized burn ratio index time series. Between 2000 and 2019, 36% of the vegetation was significantly disturbed by anthropogenic activities. The results of this study show that the disturbance trends, severity, and patterns are highly variable and strongly depend on the management approaches implemented in the heterogeneous landscape: Ruaha National Park (RNP), Rungwa–Kizigo–Muhesi Game Reserves (RKMGR), and the surrounding zones. The disturbance rates and severity were pronounced and increased toward the edges of the western RKMGR. However, the disturbance in the areas surrounding the RNP was lower. The characterization of the vegetation disturbance over time provides spatial information that is necessary for policy makers, managers, and conservationists to understand the ongoing long-term changes in large PAs.https://www.mdpi.com/2072-4292/13/9/1800vegetation disturbanceLandTrendr algorithmLandsat time-series dataconservationsavannahanthropogenic activity
collection DOAJ
language English
format Article
sources DOAJ
author Atupelye W. Komba
Teiji Watanabe
Masami Kaneko
Mohan Bahadur Chand
spellingShingle Atupelye W. Komba
Teiji Watanabe
Masami Kaneko
Mohan Bahadur Chand
Monitoring of Vegetation Disturbance around Protected Areas in Central Tanzania Using Landsat Time-Series Data
Remote Sensing
vegetation disturbance
LandTrendr algorithm
Landsat time-series data
conservation
savannah
anthropogenic activity
author_facet Atupelye W. Komba
Teiji Watanabe
Masami Kaneko
Mohan Bahadur Chand
author_sort Atupelye W. Komba
title Monitoring of Vegetation Disturbance around Protected Areas in Central Tanzania Using Landsat Time-Series Data
title_short Monitoring of Vegetation Disturbance around Protected Areas in Central Tanzania Using Landsat Time-Series Data
title_full Monitoring of Vegetation Disturbance around Protected Areas in Central Tanzania Using Landsat Time-Series Data
title_fullStr Monitoring of Vegetation Disturbance around Protected Areas in Central Tanzania Using Landsat Time-Series Data
title_full_unstemmed Monitoring of Vegetation Disturbance around Protected Areas in Central Tanzania Using Landsat Time-Series Data
title_sort monitoring of vegetation disturbance around protected areas in central tanzania using landsat time-series data
publisher MDPI AG
series Remote Sensing
issn 2072-4292
publishDate 2021-05-01
description Understanding vegetation disturbance around protected areas (PAs) is critical as it significantly affects the sustainable conservation of wildlife. However, there is a lack of analyses of consistent long-term data on vegetation disturbance. In this study, the LandTrendr algorithm and Google Earth Engine were used to access satellite data and explore the vegetation dynamics history across the Ruaha–Rungwa landscape, Tanzania. We characterized vegetation disturbance patterns and change attributes, including disturbance occurrence trends, rate, and severity, by using each pixel’s normalized burn ratio index time series. Between 2000 and 2019, 36% of the vegetation was significantly disturbed by anthropogenic activities. The results of this study show that the disturbance trends, severity, and patterns are highly variable and strongly depend on the management approaches implemented in the heterogeneous landscape: Ruaha National Park (RNP), Rungwa–Kizigo–Muhesi Game Reserves (RKMGR), and the surrounding zones. The disturbance rates and severity were pronounced and increased toward the edges of the western RKMGR. However, the disturbance in the areas surrounding the RNP was lower. The characterization of the vegetation disturbance over time provides spatial information that is necessary for policy makers, managers, and conservationists to understand the ongoing long-term changes in large PAs.
topic vegetation disturbance
LandTrendr algorithm
Landsat time-series data
conservation
savannah
anthropogenic activity
url https://www.mdpi.com/2072-4292/13/9/1800
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