scholarly journals Estimation of Peat Surface Carbon Stocks on The Semenanjung Kampar from Land Use Changes Using Landsat Multi-Temporal in 2009-2018

2019 ◽  
Vol 3 (1) ◽  
pp. 49-53
Author(s):  
Yudi Antomi ◽  
Ristalia Ristalia
Keyword(s):  
Remote Sensing ◽  
Land Use ◽  
Oil Palm ◽  
Land Use Changes ◽  
Carbon Stocks ◽  
Remote Sensing Technology ◽  
Sensing Technology ◽  
Multi Temporal ◽  
Peat Surface

Remote sensing has advantages in terms of temporal resolution that can be used to check changes in an object at different times. The Semenanjung Kampar peatland underwent land use change after the change in PP No. 71 of 2014 became PP No. 57 of 2016 which requires companies (paper companies) to restore the ecosystem on the Semenanjung Kampar. These changes were analyzed by utilizing remote sensing technology through multi-temporal imagery.This study aims to analyze changes in peatland use on the Semenanjung Kampar in 2009, 2013 and 2018, then estimate carbon stocks from changes in peatland use. The method used is the classification of Iso Cluster unsupervised and calculation of increase and decrease in carbon stocks (Gain and Loss). Based on this research the results of the accuracy of the classification of changes in land use on the Semenanjung Kampar were 0.72 or 72%.Changes in land use on the Semenanjung Kampar occur dynamically.The dominant land change for the 2009-2013 period was shrubs which became acacia forests 89386.31 ha and bushes from 2013-2018 to oil palm plantations 57878.47 ha. Furthermore, carbon stocks in the period 2009-2013 that have increased (acces) are 8.2% acacia forest and 13% decrease in primary peat forest while the 2013-2018 period has increased, namely 8% oil palm plantation and 21% shrub decline.

Based on IDRISI Remote Sensing Images Land-Use Types of Supervised Classification Techniques

2013 ◽  
Vol 415 ◽  
pp. 305-308
Author(s):  
Kun Zhang ◽  
Hai Feng Wang ◽  
Zhuang Li
Keyword(s):  
Remote Sensing ◽  
Land Use ◽  
Classification Techniques ◽  
Analysis And Evaluation ◽  
Remote Sensing Classification ◽  
Remote Sensing Technology ◽  
Sensing Technology ◽  
Remote Sensing Image Classification ◽  
Land Use Types ◽  
Area Distribution

With remote sensing technology and computer technology, remote sensing classification technology has been rapid progress. In the traditional classification of remote sensing technology, based on the combination of today's technology in the field of remote sensing image classification, some new developments and applications for land cover classification techniques to make more comprehensive elaboration. Using the minimum distance classifier extracts of the study area land use types. Ultimately extracted land use study area distribution image and make its analysis and evaluation.

scholarly journals Assessment of Land Use and Vegetative Cover in Kano Metropolis (from 1975-2015) Employing GIS and Remote Sensing Technology

2020 ◽  
Vol 27 (2) ◽  
pp. 1-7
Author(s):  
M. Haruna ◽  
M.K. Ibrahim ◽  
U.M. Shaibu
Keyword(s):  
Remote Sensing ◽  
Land Use ◽  
Agricultural Land ◽  
Landsat 8 ◽  
Vegetative Cover ◽  
Gis And Remote Sensing ◽  
Remote Sensing Technology ◽  
Sensing Technology ◽  
Agricultural Planning ◽  
Bare Land

This study applied GIS and remote sensing technology to assess agricultural land use and vegetative cover in Kano Metropolis. It specifically examined the intensity of land use for agricultural and non agricultural purpose from 1975 – 2015. Images (1975, 1995 and 2015), landsat MSS/TM, landsat 8, scene of path 188 and 052 were downloaded for the study. Bonds for these imported scenes were processed using ENVI 5.0 version. The result indicated five classified features-settlement, farmland, water body, vegetation and bare land. The finding revealed an increase in settlement, vegetation and bare land between 1995 and 2015, however, farmland decreased in 2015. Indicatively, higher percentage of land use for non agricultural purposes was observed in recent time. Conclusively, there is need to accord surveying the rightful place and priority in agricultural planning and development if Nigeria is to be self food sufficient. Keywords: Geographic Information System, Agriculture, Remote sensing, Land use, Land cover

The Quantitative Evaluation of Ecological Assets in Sanjiang Plain Based on Remote Sensing Technology

2013 ◽  
Vol 316-317 ◽  
pp. 245-249
Author(s):  
Fan Ying Meng ◽  
Zheng Hong Miao
Keyword(s):  
Remote Sensing ◽  
Land Use ◽  
Quantitative Measurement ◽  
Sanjiang Plain ◽  
Land Use Type ◽  
Remote Sensing Technology ◽  
Sensing Technology ◽  
Land Use Types ◽  
Landsat 7 ◽  
Ecological Assets

on the basis of the measurement of ecological parameters by using remote sensing technology, combined with ecological method and Landsat–7 ETM +, we made a quantitative measurement of ecological assets of Sanjiang Plain in 2010, got the spatial distribution of ecological assets. The results show that: the value of ecological assets in Sanjiang Plain was 2.35 × 1012 yuan. The value was generally higher in the southern and lower in the northern parts of the study area. Baoqing has the highest sum value and Youyi has the lowest value than other areas. Forestlands have higher value of ecological assets than other land use types. Land use type may be the mainly reason for the spatial difference of ecological assets in Sanjiang Plain.

scholarly journals Perbandingan Quadratic Discriminant Analysis dan Support Vector Machine untuk Klasifikasi Tutupan Lahan di DKI Jakarta

2020 ◽  
Vol 9 (1) ◽  
pp. 12-20
Author(s):  
Kamaluddin Junianto Dimas ◽  
Rahma Anisa ◽  
Itasia Dina Sulvianti
Keyword(s):  
Remote Sensing ◽  
Land Use ◽  
Support Vector Machine ◽  
Discriminant Analysis ◽  
Land Cover ◽  
Training Data ◽  
Support Vector ◽  
Quadratic Discriminant Analysis ◽  
Remote Sensing Technology ◽  
Sensing Technology

DKI Jakarta is a center of government as well as economy and business of Indonesia, thus development projects in Jakarta continue every year. Therefore, monitoring for land use has to be improved in accordance to DKI Jakarta Spatial Planning. The attempt needs to be supported by continuous data availability regarding land cover condition in Jakarta. The aforementioned data collecting process become easier due to remote sensing technology development. Remote sensing technology can be utilized for analyzing the size of land use area by using classification analysis. It has been found that the level of accuracy depends on the type of classification method and number of training data. This research evaluated the level of overall accuracy, sensitivity, and specificity of Quadratic Discriminant Analysis (QDA) and Support Vector Machine (SVM) along with number of data training used in classifying Jakarta land cover in 2017. The results showed that in both methods, the variance of all the aforementioned criteria were getting smaller along with the increasing number of training data. QDA and SVM had similar performance based on overall accuracy and specificity. However, SVM was better than QDA on sensitivity.

Reviewing the Pertinence of Sentinel-1 SAR for Urban Land Use Land Cover Classification

2020 ◽  
Vol 11 (5) ◽  
pp. 529-535
Author(s):  
Dan Abudu ◽  
Nigar Sultana Parvin ◽  
Geoffrey Andogah
Keyword(s):  
Remote Sensing ◽  
Land Use ◽  
Land Cover ◽  
Urban Areas ◽  
Land Use Changes ◽  
Land Cover Classification ◽  
Urban Land ◽  
Urban Land Use ◽  
Land Use Land Cover ◽  
Sensing Technology

Conventional approaches for urban land use land cover classification and quantification of land use changes have often relied on the ground surveys and urban censuses of urban surface properties. Advent of Remote Sensing technology supporting metric to centimetric spatial resolutions with simultaneous wide coverage, significantly reduced huge operational costs previously encountered using ground surveys. Weather, sensor’s spatial resolution and the complex compositions of urban areas comprising concrete, metallic, water, bare- and vegetation-covers, limits Remote Sensing ability to accurately discriminate urban features. The launch of Sentinel-1 Synthetic Aperture Radar, which operates at metric resolution and microwave frequencies evades the weather limitations and has been reported to accurately quantify urban compositions. This paper assessed the feasibility of Sentinel-1 SAR data for urban land use land cover classification by reviewing research papers that utilised these data. The review found that since 2014, 11 studies have specifically utilised the datasets.

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