Design and realization on the Object-oriented Remote Sensing Archaeological Information System

ANALISIS KESESUAIAN LAHAN DAN EVALUASI JENIS TANAH DALAM BUDIDAYA TANAMAN TEBU UNTUK PENGEMBANGAN DAERAH KABUPATEN TEGAL

Jurnal Sains dan Teknologi Indonesia ◽

10.29122/jsti.v13i2.878 ◽

2013 ◽

Vol 13 (2) ◽

Author(s):

Daru Mulyono

Keyword(s):

Remote Sensing ◽

Information System ◽

Spatial Analysis ◽

Geographical Information System ◽

Plant Productivity ◽

Saccharum Officinarum ◽

Geographical Information ◽

Sugarcane Plant ◽

Plant Cultivation ◽

Suitability Map

The objectives of the research were to make land suitability map for sugarcane plant (Saccharum officinarum), to give recommendation of location including area for sugarcane plant cultivation and to increase sugarcane plant productivity. The research used maps overlay and Geographical Information System (GIS) which used Arch-View Spatial Analysis version 2,0 A in Remote Sensing Laboratory, Agency for the Assessment and Application of Technology (BPPT), Jakarta. The research was carried out in Tegal Regency starting from June to October 2004.The results of the research showed that the suitable, conditionally suitable, and not suitable land for sugarcane cultivation in Tegal Regency reached to a high of 20,227 ha, 144 ha, and 81,599 ha respectively. There were six most dominant kind of soil: alluvial (32,735 ha), grumosol 5,760 ha), mediteran (17,067 ha), latosol (18,595 ha), glei humus (596 ha), and regosol (22,721 ha).

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Research on Object Oriented Algorithm for Road Extraction in High-Resolution Remote Sensing Image

Proceedings of the 2nd International Conference on Information Technologies and Electrical Engineering ◽

10.1145/3386415.3386963 ◽

2019 ◽

Author(s):

Yuan Fang ◽

Qifeng Che

Keyword(s):

Remote Sensing ◽

High Resolution ◽

Object Oriented ◽

Remote Sensing Image ◽

Road Extraction

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Distinguishing Planting Structures of Different Complexity from UAV Multispectral Images

Sensors ◽

10.3390/s21061994 ◽

2021 ◽

Vol 21 (6) ◽

pp. 1994

Author(s):

Qian Ma ◽

Wenting Han ◽

Shenjin Huang ◽

Shide Dong ◽

Guang Li ◽

...

Keyword(s):

Remote Sensing ◽

Confusion Matrix ◽

Object Oriented ◽

Low Complexity ◽

Classification Model ◽

Recursive Feature Elimination ◽

Support Vector ◽

Multispectral Images ◽

High Complexity ◽

Structure Complexity

This study explores the classification potential of a multispectral classification model for farmland with planting structures of different complexity. Unmanned aerial vehicle (UAV) remote sensing technology is used to obtain multispectral images of three study areas with low-, medium-, and high-complexity planting structures, containing three, five, and eight types of crops, respectively. The feature subsets of three study areas are selected by recursive feature elimination (RFE). Object-oriented random forest (OB-RF) and object-oriented support vector machine (OB-SVM) classification models are established for the three study areas. After training the models with the feature subsets, the classification results are evaluated using a confusion matrix. The OB-RF and OB-SVM models’ classification accuracies are 97.09% and 99.13%, respectively, for the low-complexity planting structure. The equivalent values are 92.61% and 99.08% for the medium-complexity planting structure and 88.99% and 97.21% for the high-complexity planting structure. For farmland with fragmentary plots and a high-complexity planting structure, as the planting structure complexity changed from low to high, both models’ overall accuracy levels decreased. The overall accuracy of the OB-RF model decreased by 8.1%, and that of the OB-SVM model only decreased by 1.92%. OB-SVM achieves an overall classification accuracy of 97.21%, and a single-crop extraction accuracy of at least 85.65%. Therefore, UAV multispectral remote sensing can be used for classification applications in highly complex planting structures.

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A Survey of Remote Sensing and Geographic Information System Applications for Flash Floods

Remote Sensing ◽

10.3390/rs13091818 ◽

2021 ◽

Vol 13 (9) ◽

pp. 1818

Author(s):

Lisha Ding ◽

Lei Ma ◽

Longguo Li ◽

Chao Liu ◽

Naiwen Li ◽

...

Keyword(s):

Remote Sensing ◽

Information System ◽

Geographic Information System ◽

Flash Flood ◽

Flash Floods ◽

Geographic Information ◽

Flood Disaster ◽

Future Research ◽

Time Zone ◽

Gis Technologies

Flash floods are among the most dangerous natural disasters. As climate change and urbanization advance, an increasing number of people are at risk of flash floods. The application of remote sensing and geographic information system (GIS) technologies in the study of flash floods has increased significantly over the last 20 years. In this paper, more than 200 articles published in the last 20 years are summarized and analyzed. First, a visualization analysis of the literature is performed, including a keyword co-occurrence analysis, time zone chart analysis, keyword burst analysis, and literature co-citation analysis. Then, the application of remote sensing and GIS technologies to flash flood disasters is analyzed in terms of aspects such as flash flood forecasting, flash flood disaster impact assessments, flash flood susceptibility analyses, flash flood risk assessments, and the identification of flash flood disaster risk areas. Finally, the current research status is summarized, and the orientation of future research is also discussed.

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