Environmental Engineering
M.K. Rosyidy; E. Frimawaty
Abstract
BACKGROUND AND OBJECTIVES: Oil palm is one of the crops that has an essential role in Indonesia's engineering field. This condition has led to oil palm plantation intensification, which has been extensive to deforestation in Indonesia, including Jambi province. The main aim of this investigation is to ...
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BACKGROUND AND OBJECTIVES: Oil palm is one of the crops that has an essential role in Indonesia's engineering field. This condition has led to oil palm plantation intensification, which has been extensive to deforestation in Indonesia, including Jambi province. The main aim of this investigation is to evaluate deforestation and land change affected by oil palm expansion conducted by smallholders, which influences environmental change using remote sensing combined with a geographic information system approach. This study utilizes the change of oil Palm in spatial-temporal (spatial and temporal) in Jambi province related to land change and environmental impacts.METHODS: This research uses data from Landsat 8 satellite imagery. The land cover classification was done using the Maximum Likelihood approach, while the overlay method was used for land change analysis. Accuracy assessment of classification results uses a confusion matrix taking into account overall accuracy and Kappa Hat. Within the field observation, the validation class is the oil palm class, using documentation and plotting using the global positioning system, and other classes are validated using the Region of Interest collected through Google Earth. This research uses Aviation Reconnaissance Coverage Geographic Information System 10.1 software to transform the categorization results into vector data. FINDINGS: This study shows that the landcover classification results have high accuracy. This study shows that the area of oil palm land from 2015 to 2019 has increased along with a decrease in land used, such as forests and others. The area of oil palm land 2014 was 2,071,345 hectares, while the area in 2019 was 2,110,545 hectares. In other words, there was an increase in land cover due to land clearing and deforestation, namely 39.2 thousand hectares. The built-up area has also increased in the last five years, namely 165,358 hectares. The number of oil palm plantations tends to be greater in relatively plain areas compared to areas with relatively high altitudes and steep slopes. Small farmers'''' area of oil palm land increased by 1,000 hectares in 2014-2018. The most significant increase occurred in 2016-2017, around 38,889 hectares.CONCLUSION: This study demonstrates that using Landsat 8 imagery combined with GIS approaches provides the optimal method for an in-depth analysis of land cover changes related to oil palm expansion and land clearing that occur on a broader spatial scale and temporal in Jambi Province. This study shows that smallholder oil palm plantations in the Jambi region play an important role in increasing deforestation in Jambi Province, especially in Indonesia. This study is expected to serve as a valuable resource for informing policy decisions aimed at addressing the issue of deforestation resulting from the prospective increase of oil palm crops in the forthcoming period.
Environmental Management
C. Payus; J. Sentian
Abstract
BACKGROUND AND OBJECTIVES: This study analyzed the changes in land use and land cover trends and their implication on malaria transmission using satellite imagery applications. Deforestation or human land use activity related to water and development has expanded the ideal habitats for malaria-carrying ...
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BACKGROUND AND OBJECTIVES: This study analyzed the changes in land use and land cover trends and their implication on malaria transmission using satellite imagery applications. Deforestation or human land use activity related to water and development has expanded the ideal habitats for malaria-carrying mosquitoes, resulting in an upsurge of malaria transmission.The presence of these habitats and breeding increased the contact between humans and mosquitoes, thus increasing the number of malaria cases. The decrease of canopy and forest cover has increased the temperature, resulting in the shortening of aquatic stages and sporogony development of the mosquitoes. This study aims to provide an understanding of the relationship between the topography effect over the land-use factor and land cover change on malaria for more than ten years from 2005 to 2019 of transmission.METHODS: Malaria case data obtained were analyzed for the trends, incidence rate, and spatial distribution. Remote Sensing and geographic information system were used to determine the land use and land cover change in selected districts of North Borneo in Sabah, as the study areas.FINDING: The malaria incidence rate shows an increase from 2005 to 2019, with 149.64%. The transmission of the malaria vector dynamics and abundance with topography changes has changed with time, including with forest declination at 8.38%, and cropland change decreased at 16.61%. However, an expansion of 33.6% was observed for oil palm plantations. Overall, the results have shown that the range of incidence rate was found` highly viable from 0.29/1000 persons to 4.09/1000 people.CONCLUSION: In conclusion, using geographic information system remote sensing with malaria integrated topography transmission information will be targeted by zoning most affected areas or the most productive larval habitat for remedial measures. This study can help to reduce the malaria vector population through environmental management related to the mosquito larval cycle in different land-use settings and change by minimizing the transmission by the targeted malaria control program.
Environmental Engineering
G.R. Puno; R.C.C. Puno; I.V. Maghuyop
Abstract
BACKGROUND AND OBJECTIVES: Fine topographic information is a key input parameter for a detailed flood simulation and mapping. This study aimed to compare the accuracy statistics of the flood models developed using the digital elevation datasets with different resolutions from the light detection and ...
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BACKGROUND AND OBJECTIVES: Fine topographic information is a key input parameter for a detailed flood simulation and mapping. This study aimed to compare the accuracy statistics of the flood models developed using the digital elevation datasets with different resolutions from the light detection and ranging and interferometric synthetic aperture radar systems.METHODS: The study applied the Hydrologic Engineering Center-Hydrologic Modeling System and Hydrologic Engineering Center-River Analysis System models workable within the geographic information system to simulate and map flood hazards in Maapag Watershed. The models’ validity and accuracy were tested using the confusion error matrix, f-measurement, and the root means square error statistics.FINDINGS: Results show that using the light detection and ranging dataset, the model is accurate at 88%, 0.61, and 0.41; while using the interferometric synthetic aperture radar dataset, the model is accurate at 76%, 0.34, 0.53; for the error matrix, f-measurement, and root mean square error; respectively.CONCLUSION: The model developed using the light detection and ranging dataset showed higher accuracy than the model developed using the interferometric synthetic aperture radar. Nevertheless, the latter can be used for flood simulation and mapping as an alternative to the former considering the cost of model implementation and the smaller degree of accuracy residual error. Hence, flood modelers particularly from local authorities prefer to use coarser datasets to optimize the budget for flood simulation and mapping undertakings.
Environmental Management
G. R. Puno; R. C. Puno; I. V. Maghuyop
Abstract
BACKGROUND AND OBJECTIVES: The study involved developing a two-dimensional flood model to analyze the risk exposure of land use/land cover based on the generated flood hazard maps for the six return period scenarios in the Solana watershed.METHODS: The approach consisted of applying hydrologic and hydraulic ...
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BACKGROUND AND OBJECTIVES: The study involved developing a two-dimensional flood model to analyze the risk exposure of land use/land cover based on the generated flood hazard maps for the six return period scenarios in the Solana watershed.METHODS: The approach consisted of applying hydrologic and hydraulic numerical flood models and the suite of advanced geographic information systems and remote sensing technologies. The process involved utilizing a high-resolution digital elevation model and a set of high-precision instruments such as the real-time kinematic-global position system receiver, digital flow meter, deep gauge, and automatic weather station in collecting the respective data on bathymetry, river discharge, river depth, and rainfall intensity during a particular climatic event, needed for the model development, calibration and validation.FINDINGS: The developed two-dimensional flood model could simulate flood hazard with an 86% accuracy level based on the coefficient of determination statistics. The flood risk exposure analysis revealed that coconut is the most affected, with 31.3% and 37.1% being at risk across the 2-year and 100-year return period scenarios, respectively. Results also showed that rice and pineapple are at risk of flooding damage with the increasing rate of exposure by a magnitude of 42.9 and 9.3 across the 2-year and 100-year flood scenarios, respectively.CONCLUSION: The study highlighted the integration of the findings and recommendations in the localized comprehensive land use plan and implementation to realize the challenge of building a climate change proof and a flood-resilient human settlement in the urbanizing watershed of Solana.
A. Azizi; B. Malakmohamadi; H.R. Jafari
Abstract
Analyzing the process of land use and cover changes during long periods of time and predicting the future changes is highly important and useful for the land use managers. In this study, the land use maps in the Ardabil plain in north-west part of Iran for four periods (1989, 1998, 2009 and 2013) are ...
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Analyzing the process of land use and cover changes during long periods of time and predicting the future changes is highly important and useful for the land use managers. In this study, the land use maps in the Ardabil plain in north-west part of Iran for four periods (1989, 1998, 2009 and 2013) are extracted and analyzed through remote sensing technique, using the land-sat satellite images. Then, the future land use changes are simulated for 2030 using integrated CA-Markov model according to the scenario of continuing current management process. The results show that in the period between 1989 and 2009, i.e. since two-thirds of the plain was declared restricted till all of it was declared thus, the study area has experienced a total of about 58645.08 ha changes. After the whole plain was restricted (since 2009 till 2014), the changes have been estimated to be 22466.88 ha. The prediction also indicates that the changes will equal 8908.83 ha by 2030. Agricultural lands and human-built environment constitute the majority of changes and are increasing continuously. The obtained Kappa values for the model accuracy assessment (higher than 0.8) indicated the model's capability to predict future Land use/cover changes in the study area. Thus, analyzing Land use and cover changes trends from past to near future using CA-Markov model can play a significant role in land use policy making, planning, and managing of the restricted plains especially in the proposed study area.