Dynamics land cover changes of Wulan Delta in 2003-2017 approach by remote 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.

Download Full-text

Time Series Analysis of Land Cover Using Remote Sensing Technology

Journal of Computational and Theoretical Nanoscience ◽

10.1166/jctn.2020.8739 ◽

2020 ◽

Vol 17 (2) ◽

pp. 902-910

Author(s):

Ahmad Taufiq Hosni ◽

Suharto Teriman ◽

Nor Aizam Adnan ◽

Muhamad Asri Abdullah Kamar

Keyword(s):

Remote Sensing ◽

Land Cover ◽

Urban Areas ◽

Management Plan ◽

Urban Environments ◽

Lulc Changes ◽

Remote Sensing Technology ◽

Sensing Technology ◽

Development Area ◽

Landsat Satellite

The observation of land use/land cover (LULC) is essential as it allows humans to investigate the alteration of land which occurs over a period of time. This is to allow mankind to have a proper management of the earth resources and well planned development. One way to observe LULC is by using remote sensing technology since it provides continuous data monitoring of the earth’s surface. This study is carried out at Bandar Meru Raya, Ipoh, Perak and aimed to quantify the LULC changes, especially in urban areas which occurred within two decades from 1995 to 2005 and from 2005 to 2015. Maximum likelihood supervised classification was performed on three Landsat satellite imageries using ERDAS Imagine 2014 software. The images were classified into 4 general LULC categories namely forest, development area, green area, and water bodies. The results indicated that a considerable amount of forested area was decreasing by 183.12 hectares within the last 20 years while development area gained a total of 157.12 hectares. This LULC changes showed a serious loss of trees and this sort of change tends to affect the nature’s ecosystem. Therefore, by quantifying the loss of forest area will enable authorities to oversee and plan a better management of trees for future in urban environments. Such management plan is necessary in order to maintain the importance of trees towards nature and community.

Download Full-text

A Novel Remote Sensing Technology on Land Analysis Use Change Detection

Asian Journal of Computer Science and Technology ◽

10.51983/ajcst-2019.8.3.2733 ◽

2019 ◽

Vol 8 (3) ◽

pp. 10-14

Author(s):

J. Suresh Babu ◽

T. Sudha

Keyword(s):

Land Use ◽

Land Cover ◽

Ground Truth ◽

Soil Protection ◽

Land Cover Changes ◽

Remote Sensing Technology ◽

Picture Arrangement ◽

Sensing Technology ◽

Erdas Imagine ◽

Extreme Probability

Change location is helpful in numerous applications identified with land use and land cover changes, for example, moving development and scene changes, arrive corruption and desertification. Remotes sensing technology has been utilized for the location of the adjustment in land use arrive cover in upper Rib watershed. The fundamental target of this examination was to identify the land use change utilizing Remotes sensing for manageable land use arranging in Upper Rib watershed. The two satellite pictures for the year 2007 and 2018 were downloaded and utilized for recognizing the land cover changes. Most extreme probability arrangement was utilized in ERDAS Imagine device for characterizing the pictures. Ground truth focuses were gathered and utilized for check of picture arrangement. This was identified with the proceeded with extension of developed and settlement over years in River watershed. The information about the adjustment in land use is so fundamental for the organization and land use arranging exercises in upper Rib watershed. This is so for, the expansion and profitability of Rib repository by decreasing the upland disintegration through powerful land use arranging and soil preservation rehearses. Consequently, this examination uncovered that there is an expansion of horticultural land which needs due consideration towards soil protection for the improvement of the helpful existence of the supply.

Download Full-text

Study on land use/land cover change in Jintai and Weibing districts of Baoji city in Western China based on remote sensing technology and Markov method

Journal of Applied Remote Sensing ◽

10.1117/1.3159400 ◽

2009 ◽

Vol 3 (1) ◽

pp. 033534 ◽

Cited By ~ 2

Author(s):

Xiaoyan Dai

Keyword(s):

Remote Sensing ◽

Land Use ◽

Land Cover ◽

Land Cover Change ◽

Western China ◽

Land Use Land Cover ◽

Remote Sensing Technology ◽

Sensing Technology ◽

Markov Method

Download Full-text

ANALISIS SPASIAL SEBARAN LAHAN KRITIS DI KPHP UNIT XII BATANGHARI PROVINSI JAMBI

Jurnal Belantara ◽

10.29303/jbl.v4i2.820 ◽

2021 ◽

Vol 4 (2) ◽

pp. 127

Author(s):

Eva Achmad ◽

Agus Kurniawan ◽

Yunita Lestari

Keyword(s):

Land Cover ◽

Critical Level ◽

Land Cover Changes ◽

Landsat 8 ◽

Maximum Score ◽

Gis And Remote Sensing ◽

Remote Sensing Technology ◽

Sensing Technology ◽

Forest Function ◽

Slope Class

Critical land occured as a result of land cover changes from vegetated into non vegetated land or the composition of the vegetation has changed. This study aimed to analyze the distribution of land critical at KPHP Unit XII Batanghari. Critical land analysis was based on the Perdirjen PDASHL Number P.3/PDASHL/SET/KUM.1/7/2018. Land is classified into 5 levels of criticality, namely: non-critical, critical potential, somewhat critical, critical and very critical. The parameters used in determining the level of criticality of the land are: land cover, erosion-prone class, slope class and the presence of land inside or outside the forest function. Spatial analysis used by Geographic Information System (GIS) and remote sensing technology. GIS is able to analyze and represent geographic phenomenon. Landsat 8 imagery was analyzed to obtain land cover clasification. The results of the analysis showed that critical land level of KPHP Unit XI Batanghari consisted of 3,609 ha (4.45%) that classified as very critical and 3,599 ha (4,43%) as critical land. Then, land with a somewhat critical level had the largest area, namely 26,024 ha or 32.07% of the total area of KPHP Unit XII Batanghari. The landcover was the main parameter to determine the level of criticality of the land. The openland cover type had the maximum score 60.

Download Full-text