Assessment of the successfulness of mangrove plantation program through the use of open source software and freely available satellite

Abstract

Nursamsi I, Komala WR.2017. Assessment of the successfulness of mangrove plantation program through the use of open source software and freely available satellite images. Nusantara Bioscience 9: 251-259. Mangrove forest has a major role in the process of human-environment interaction, but almost every mangrove forest in the world is under threat. In Indonesia alone, 25% of South East Asia’s mangroves are at a risk. The continued decline in mangrove forest induced by anthropogenic activity has made all the stakeholders who have the concern at the mangrove forest preservation worried, including the government. There were several programs have been performed by the government to preserve the mangrove forest. One of the programs was “Mangrove Rehabilitation Program in three districts: Ciamis, Indramayu, and Subang” held by Forestry Department of West Java Province in 2007. The aims of this study were to assess the changes in mangrove forest area before the program performed and to evaluate the successfulness of the program, using the increasing of mangrove forest area as a parameter. This study was conducted only in Subang and Indramayu Districts of West Java, Indonesia. The assessment was conducted using Landsat 4-5 TM, Landsat 7 ETM+, and Landsat 8 OLI acquired in 1996, 2006, and 2016 respectively. For each image, a supervised classification method was performed using open source GRASS GIS software. The resulting maps were then compared to quantify the changes. Field work activity conducted and confirmed the changes that occurred in the study areas. Our study shows that all of the two districts exhibit successfulness of the plantation program. Ground truth survey confirmed that the successfulness of the plantation program is due to the participation of communities in the area of study. This study also shows that by using open source software and freely available satellite images, the fast, robust, and reliable data as an initial step to monitor both short-term and long-term plantation program can be collected effectively and inexpensively.

Remote Sensing of Human–Environment Interactions in Global Change Research: A Review of Advances, Challenges and Future Directions

“…Studies that assess vegetation dynamics or deforestation commonly use proxies for vegetation health such as the Normalized Difference Vegetation Index (NDVI) [27,[50][51][52]54,[57][58][59][67][68][69][70][71][72] or Disturbance Index [47], or through overall LUCC assessment to quantify changes in aerial extents of forest [32,40,56,73,74]. NDVI has been incorporated into studies for a variety of purposes.…”

“…While NDVI is the most widely employed index based on our search, other indices have been utilized to study changes in vegetation or vegetation condition including SAVI (soil adjusted vegetation index), NDWI (normalized difference water index), MCARI (modified chlorophyll absorption in reflectance index), CAI (cellulose adsorption index), LWVI2 (leaf water vegetation index), NDLI (normalized difference lignin index), NDNI (normalized difference nitrogen index), and MSI (moisture stress index) and others. Nursamsi & Komala [72] used both NDVI and NDWI to assess the success of mangrove forest rehabilitation because the NDWI is sensitive to changes in the water content of canopies and can help enhance the presence of vegetation in remotely sensed imagery. Leitao et al [27] used NDVI in combination with MCARI, LWVI2, CAI, NDLI, and NDNI to characterize vegetation condition and cover at the sub-pixel level.…”

“…Studies focusing on urban land use and human-environment dynamics in urban systems were also common during the last two decades and addressed a range of topics including quantification of impervious areas [82], vegetation cover or dynamics [33,83,84], urbanization or urban growth trends [29,85], or the use of thermal imaging for urbanization effects on land surface temperature [37,69,86]. The research by Tagil et al [87] was framed in an ecological context and used remote sensing in conjunction with other methods to understand urban landscape dynamics and urban ecosystem changes [72]. There were several common themes among urban studies, including the utility of integrating remote sensing, GIS, and socio-economic data for sustainable urban planning and development [29,[87][88][89].…”

“…Regional and local processes have significant implications for household vulnerability [91], thus the study and management of socio-ecologic systems should be conducted with stakeholders in mind not only within the domains of HEI and HDGC. Emerging or underutilized methodologies and technologies such as thermal sensing [105,106], digital soil mapping [107], citizen science [72,108], UAVs, cloud computing, mobile mapping [108], or the use of "humans as sensors" [109,110] can guide informed decision-making in areas where data is hard to collect due to variability in socio-ecological settings [108] and will enhance the relevancy of future HDGC and HEI studies. The ability to run fast and complex computations based on long timeseries of remote sensing and environmental data in virtual or cloud-based environments such as Google Earth Engine or other National Aeronautical and Space Agency applications (Application for Extracting and Exploring Analysis Ready Samples-AppEEARS), for instance, will likely open up the specialized field of remote sensing to more social science applications and integrations.…”

Thirty-two years of mangrove forest land cover change in Parita Bay, Panama

“…However, the global rate of mangrove loss has declined overtime, and the carbon losses have reduced due to conservation policies, restoration projects, and the natural regeneration of mangrove species (Giri et al 2011;Hamilton and Casey 2016;Thomas et al 2017). Some studies have also reported increasing trends of mangrove forests in different parts of the world (Nursamsi and Komala 2017;Hsu and Lee 2018;Wang et al 2018). It is, therefore, necessary to adequately monitor the dynamics of mangrove ecosystems to further understand their behavior, resilience, and future risks so that effective coastal adaptation and conservation policies can be implemented (e.g.…”