The mangrove ecosystem plays a vital role in the global carbon cycle, by reducing greenhouse gas emissions and mitigating impacts of climate change. However, mangroves have been lost worldwide, resulting substantial stock losses. Additionally, some aspects remain poorly characterized compared to other forest ecosystems due practical difficulties measuring monitoring biomass their stocks. Without quantitative method for effectively biophysical parameters stocks mangroves, robust policies...

Principal component analysis (PCA) is one of the most commonly adopted feature reduction techniques in remote sensing image analysis. However, it may overlook subtle but useful information if applied directly to hyperspectral data, especially for discriminating between different vegetation types. In order accurately map an invasive plant species (horse tamarind, Leucaena leucocephala) southern Taiwan using Hyperion imagery, this study developed a spectrally segmented PCA based on spectral...

Aboveground biomass (AGB) of mangrove forest plays a crucial role in global carbon cycle by reducing greenhouse gas emissions and mitigating climate change impacts. Monitoring forests accurately still remains challenging compared to other ecosystems. We investigated the usability machine learning techniques for estimation AGB plantation at coastal area Hai Phong city (Vietnam). The study employed GIS database support vector regression (SVR) build verify model AGB, drawing upon data from...

This study tested the use of machine learning techniques for estimation above-ground biomass (AGB) Sonneratia caseolaris in a coastal area Hai Phong city, Vietnam. We employed GIS database and multi-layer perceptron neural networks (MLPNN) to build verify an AGB model, drawing upon data from survey 1508 mangrove trees 18 sampling plots ALOS-2 PALSAR imagery. assessed model's performance using root-mean-square error, mean absolute coefficient determination (R2), leave-one-out...

This research examined mangrove management in Hai Phong city, Vietnam. A combination of logistic regression model data and field survey were used to investigate the driving forces changes. The results indicate that implementation investigated by authorities, community or local people has affected change. main force loss is over expansion shrimp aquaculture. poorer families would like participate conservation activities more than richer households. Mangrove rehabilitation programs have been...

This study examined the potential of using HH and HV backscatter from Advanced Land Observing Satellite 2 (ALOS-2) with enhanced phased array L-band synthetic aperture radar (PALSAR) in high sensitive mode to estimate above-ground biomass (AGB) two mangrove species Hai Phong city, Vietnam. A positive correlation was observed between mean backscattering coefficients dominant at dual polarizations various biophysical parameters. In contrast, low correlations were those tree densities for...

Improving the understanding of land use and cover is a major research challenge for human-environmental sciences essential many aspects global environmental research. Considering seasonal vegetation dynamics or phenological in multi-year series leads to broader view cover. This study based on hypothesis that pixel representing complex but consistent has typical, distinct repeated temporal pattern index inter-annually, which can be used as characteristic signatures classification. events...

Accurate information of paddy fields over wide areas is essential to support sustainable agricultural and a food security program. Monitoring these lands continuously, using remote sensing technology, will provide related the cropping intensity in field, as well its dynamics change. We characterized seasonal vegetation from long-term multi-temporal MODIS satellite datasets order determine analyze change field Java. The results indicate that methodology employed this research distinguished...

This study examined the driving forces of mangrove change and compared forest management mechanisms in coastal districts Hai Phong city, Vietnam. Survey data was used to ascertain change. The market price approach analyze how local people responded conservation. results indicated that implementation instigated by authorities, community or has affected main factor degradation over expansion shrimp aquaculture. In Trang Cat commune, An district, average size ponds where controlled people,...

Simultaneous analysis of land surface attributes and their seasonal changes provides a broader view land-use land-cover change. This study attempted to detect the change in inter-annual temporal vegetation dynamics, which reflects attributes. We explored 250-m multi-temporal MODIS EVI 16-day composite data from 2001 2007 characterize dynamics related detection. The was filtered time-frequency space by wavelet function order identify reduce overall noise so as not lose useful information time...

Pisco was the area most damaged by 2007 Peru earthquake. The purpose of this research is to develop possibilities using satellite imagery monitor postdisaster urban recovery processes, focusing on change in between and 2011. To end, authors carried out field surveys city 2012 2013 also examined previous determine that building reconstruction peaked 2008 2009. After analyzing five-year process, compared its conditions visual interpretation with those image analysis image. An accuracy 71.2%...

Abstract. Remote sensing has long been used as a means of detecting and classifying changes on the land. Analysis multi-year time series land surface attributes their seasonal change indicates complexity use cover (LULCC). This paper explores temporal considering vegetation dynamics, in other words, distinguishing regarding to properties long-term image analysis. study is based hypothesis that might be dynamics; however, consistent typical, distinct repeated pattern index inter-annually....