Land use and land cover change monitoring in the Source Region of Yellow River by remote sensing technology

2011 ◽  
Author(s):  
Guangyin Hu ◽  
Zhibao Dong ◽  
Junfeng Lu ◽  
Changzhen Yan
Keyword(s):  
Remote Sensing ◽  
Land Use ◽  
Land Cover ◽  
Land Cover Change ◽  
Yellow River ◽  
Source Region ◽  
Remote Sensing Technology ◽  
Sensing Technology ◽  
Change Monitoring

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.

scholarly journals Analysis of Land Use and Land Cover Changing Patterns of Bangladesh Using Remote Sensing Technology

2021 ◽  
Vol 17 (3) ◽  
pp. 64-74
Author(s):  
Md. Mahmudul Hasan ◽  
Rashidul Islam ◽  
Md. Saifur Rahman ◽  
Md. Ibrahim ◽  
Md. Shamsuzzoha ◽  
...  
Keyword(s):  
Remote Sensing ◽  
Land Use ◽  
Land Cover ◽  
Remote Sensing Technology ◽  
Sensing Technology ◽  
Changing Patterns

Assessment of land cover change and desertification using remote sensing technology in a local region of Mongolia

2016 ◽  
Vol 57 (1) ◽  
pp. 64-77 ◽  
Author(s):  
Munkhnasan Lamchin ◽  
Jong-Yeol Lee ◽  
Woo-Kyun Lee ◽  
Eun Jung Lee ◽  
Moonil Kim ◽  
...  
Keyword(s):  
Remote Sensing ◽  
Land Cover ◽  
Land Cover Change ◽  
Local Region ◽  
Remote Sensing Technology ◽  
Sensing Technology

A Study of Lake Wetland Information Automatic Extraction Based on the Interpolation and Threshold Method

2012 ◽  
Vol 433-440 ◽  
pp. 6674-6677
Author(s):  
Zhi Hong An ◽  
Yong Jun Sun ◽  
De Zhi Chen ◽  
Yun Feng Qiu
Keyword(s):  
Remote Sensing ◽  
Yellow River ◽  
Source Region ◽  
Structural Features ◽  
Automatic Extraction ◽  
Threshold Method ◽  
Remote Sensing Technology ◽  
Sensing Technology ◽  
Human Material ◽  
Yellow River Source

Lake is one of the most type important wetland; remote sensing technology applied on wetland had become a research hotspot of wetlands. Automatic or semi-automatic extraction using computer wetland information extraction can improve the efficiency in the human, material, etc. From remote sensing images automatically extract wetland information is important for Wetland research and putting forward Utilization. In this paper, Yellow River source region for the test area, we use interpolation and threshold method automatically to extract lake information from ETM + images. Making use of both spectral and structural features of lake, this method acquired a good result.

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