Land use/land cover changes in the coastal zone of Ban Don Bay, Thailand using Landsat 5 TM data

Muttitanon, W.; Tripathi, Nimisha

doi:10.1080/0143116051233132666

Cited by 207 publications

(117 citation statements)

References 8 publications

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“…The NDVI, derived from the red and near-infrared bands of a multispectral image, has been widely used to separate vegetation from non-vegetation and mangrove from non-mangrove areas [236][237][238]. Canopy-closure charts or density maps provide additional information on the dynamics of mangrove biomass and health status [199,234,239,240].…”

Section: Mangrovesmentioning

confidence: 99%

Multiple Stable States and Catastrophic Shifts in Coastal Wetlands: Progress, Challenges, and Opportunities in Validating Theory Using Remote Sensing and Other Methods

et al. 2015

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Multiple stable states are established in coastal tidal wetlands (marshes, mangroves, deltas, seagrasses) by ecological, hydrological, and geomorphological feedbacks. Catastrophic shifts between states can be induced by gradual environmental change or by disturbance events. These feedbacks and outcomes are key to the sustainability and resilience of vegetated coastlines, especially as modulated by human activity, sea level rise, and climate change. Whereas multiple stable state theory has been invoked to model salt marsh responses to sediment supply and sea level change, there has been comparatively little empirical verification of the theory for salt marshes or other coastal wetlands. Especially lacking is long-term evidence documenting if or how stable states are established and maintained at ecosystem scales. Laboratory and field-plot studies are informative, but of necessarily limited spatial and temporal scope. For the purposes of long-term, coastal-scale monitoring, remote sensing is the best viable option. This review summarizes the above topics and highlights the emerging promise and challenges of using remote sensing-based analyses to validate coastal OPEN ACCESS Remote Sens. 2015, 7 10185 wetland dynamic state theories. This significant opportunity is further framed by a proposed list of scientific advances needed to more thoroughly develop the field.

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Section: Mangrovesmentioning

confidence: 99%

Multiple Stable States and Catastrophic Shifts in Coastal Wetlands: Progress, Challenges, and Opportunities in Validating Theory Using Remote Sensing and Other Methods

et al. 2015

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“…Among the several classifiers available, the Maximum Likelihood Classifier (MLC) has been widely used to classify RS data and successful results of applying this classifier for land-cover mapping have been numerous (e.g., [18][19][20]) despite the limitations due to its assumption of normal distribution of class signatures [21]. Its use has also been effective in a number of post-classification comparison change detection studies (e.g., [12,[22][23][24]). While recent studies have indicated the superiority of newly developed image classification techniques based on Decision Trees (DT), Neural Networks (NN) and Support Vector Machines (SVM) over MLC (e.g., [25][26][27][28]), the advantage of MLC over these classifiers is significant owing to its simplicity and lesser computing time.…”

Section: Rs Change Detectionmentioning

confidence: 99%

Integrated Landsat Image Analysis and Hydrologic Modeling to Detect Impacts of 25-Year Land-Cover Change on Surface Runoff in a Philippine Watershed

2011

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Landsat MSS and ETM+ images were analyzed to detect 25-year land-cover change in the critical Taguibo Watershed in Mindanao Island, Southern Philippines. This watershed has experienced historical modifications of its land-cover due to the presence of logging industries in the 1950s, and continuous deforestation due to illegal logging and slash-and-burn agriculture in the present time. To estimate the impacts of land-cover change on watershed runoff, land-cover information derived from the Landsat images was utilized to parameterize a GIS-based hydrologic model. The model was then calibrated with field-measured discharge data and used to simulate the responses of the watershed in its year 2001 and year 1976 land-cover conditions. The availability of land-cover information on the most recent state of the watershed from the Landsat ETM+ image made it possible to locate areas for rehabilitation such as barren and logged-over areas. We then created a "rehabilitated" land-cover condition map of the watershed (re-forestation of logged-over areas and agro-forestation of barren areas) and used it to parameterize the model and predict the runoff responses of the watershed. Model results showed that changes in land-cover from 1976 to 2001 were directly related to the significant increase in surface runoff. Runoff predictions showed that a full rehabilitation of the watershed, especially in barren and logged-over areas, will be likely to reduce the generation of a huge volume of runoff during rainfall events. The results of this study have OPEN ACCESSRemote Sens. 2011, 3 1068 demonstrated the usefulness of multi-temporal Landsat images in detecting land-cover change, in identifying areas for rehabilitation, and in evaluating rehabilitation strategies for management of tropical watersheds through its use in hydrologic modeling.

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“…Tujuan proses pengesanan perubahan LULC menerusi imej digital adalah untuk mengenal pasti perubahan ciri penting antara dua atau lebih selang masa (Muttitanon & Tiipathi 2005). Terdapat banyak teknik yang dibangunkan untuk mengesan perubahan LULC, misalnya menerusi teknik perbandingan imej pasca klasifikasi, pembezaan imej, menggunakan nisbah imej, regresi imej, pendigitan secara manual pada skrin paparan kawasan perubahan hasil daripada teknik analisis komponen utama dan klasifikasi imej multi-tarikh (Lu et al 2005).…”

Section: Pengenalanunclassified

Analisis Perubahan Guna Tanah dan Litupan Bumi di Gombak, Selangor Menggunakan Data Penderiaan Jauh

Choy¹

2016

JSM

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The purpose of this study was to examine the land use and land cover changes (LULC) in Gombak, Selangor by using remote sensing approach. Comparison of time series data between years of 1989-1999, 1999-2014 and 1989-2014 LULC, accounted for -47.73% for the year 1989LULC, accounted for -47.73% for the year /1999LULC, accounted for -47.73% for the year , while 1999LULC, accounted for -47.73% for the year -2014 showed that the built-up area has the highest changes at +44.53% and for the year 1989-2014 rubber has the highest change value at -34.6%. The decline of rubber in Gombak can be attributed to the increasing of built-up area which has taken over the agricultural area. In general, the pattern of LULC in Gombak is in line with the expansion and implementation of development by the local authorities.

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Land use/land cover changes in the coastal zone of Ban Don Bay, Thailand using Landsat 5 TM data

Cited by 207 publications

References 8 publications

Multiple Stable States and Catastrophic Shifts in Coastal Wetlands: Progress, Challenges, and Opportunities in Validating Theory Using Remote Sensing and Other Methods

Multiple Stable States and Catastrophic Shifts in Coastal Wetlands: Progress, Challenges, and Opportunities in Validating Theory Using Remote Sensing and Other Methods

Integrated Landsat Image Analysis and Hydrologic Modeling to Detect Impacts of 25-Year Land-Cover Change on Surface Runoff in a Philippine Watershed

Analisis Perubahan Guna Tanah dan Litupan Bumi di Gombak, Selangor Menggunakan Data Penderiaan Jauh

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