scholarly journals Mangrove Conservation Strategy in Bedono Village, Sayung District, Demak Regency Based on Remote Sensing Satellite Data

2019 ◽  
Vol 125 ◽  
pp. 02010
Author(s):  
Atmari ◽  
Denny Nugroho Sugianto ◽  
Fuad Muhammad
Keyword(s):  
Remote Sensing ◽  
Natural Resources ◽  
Satellite Data ◽  
Remote Sensing Data ◽  
Mangrove Ecosystem ◽  
Conservation Strategy ◽  
Government Agencies ◽  
Remote Sensing Technology ◽  
Sensing Technology ◽  
Mangrove Conservation

The mangrove ecosystem is an ecosystem unit in the form of a stretch containing biological natural resources dominated by trees that grow in coastal areas and river estuaries and is influenced by tides. The purpose of this study was to determine the vegetation in Bedono Village, Sayung District, Demak Regency by using remote sensing technology for conservation. Remote sensing technology has recently been used by government agencies or non-government agencies because it is considered more effective and efficient. Based on remote sensing data, the mangrove ecosystem in Bedono Village, Sayung Subdistrict, Demak Regency experienced an increase in the category of moderate and heavy mangroves in 2004-2009.

Information Extraction and Metallogenic Prediction of Qiangduo Area in Tibet Based on Multi-Source Remote Sensing Data

2014 ◽  
Vol 962-965 ◽  
pp. 127-131
Author(s):  
Xin Xing Liu
Keyword(s):  
Remote Sensing ◽  
Remote Sensing Data ◽  
Geological Mapping ◽  
Advanced Technology ◽  
Data Types ◽  
Sensing Data ◽  
Advantages And Disadvantages ◽  
Remote Sensing Technology ◽  
Sensing Technology ◽  
Metallogenic Prediction

Remote sensing technology as a kind of new and advanced technology has been playing an important role in geological mapping and prospecting. A single kind of remote sensing data always has both advantages and disadvantages. And with multispectral remote sensing data types increasing, the integrated application of multi-source remote sensing data will be one of the development trend of remote sensing geology. In this paper, comprehensive utilization of multi-source remote sensing data such as ETM+, ASTER, Worldview-II and DEM, lithology and geological structure of Qiangduo area in Tibet were interpreted in different levels and mineralized alteration information also was extracted. Then on the basis of modern metallogenic theory, analyzed the multiple mineralization favorite information, established the remote sensing prediction model, and on the GIS platform, carried out metallogenic prediction of the study area. The field validation shows that the results of the prediction are relatively accurate and remote sensing technology can improve the efficiency of geological work.

Assessment on 2000-2010 Ecosystem Function Changes of Yiwulvshan National Nature Scenic Area

2014 ◽  
Vol 1051 ◽  
pp. 489-494
Author(s):  
Xiao Chen Wang ◽  
Jing Hai Zhu ◽  
Yuan Man Hu ◽  
Wei Ling Liu
Keyword(s):  
Remote Sensing ◽  
Ecosystem Function ◽  
Primary Productivity ◽  
Water Conservation ◽  
Net Primary Productivity ◽  
Remote Sensing Data ◽  
Vegetation Coverage ◽  
The Past ◽  
Remote Sensing Technology ◽  
Sensing Technology

Based on the remote-sensing data and ground data, this study is conducted on the ecosystem function of Yiwulvshan National Nature Scenic Area (hereinafter as “Yiwulvshan Scenic Area”) from 2000 to 2010 with the GIS (geographic information system) and RS (remote sensing) technology, so as to provide reference for better environmental protection of the scenic area. It is shown from the results that there is no obvious change of land use in Yiwulvshan Scenic Area; while the capacity for soil and water conservation is slightly improved mainly due to increase of vegetation coverage; the vegetation net primary productivity declines somewhat about 5.27% in past 10 years; and biodiversity is slightly increased. As a whole, the ecosystem function of Yiwulvshan Scenic Area basically kept stable in the past 10 years, which indicated that the existing regulations can effectively protect the ecological function of the Scenic Area.

Advances in remote sensing technologies for forest surveys and management

1990 ◽  
Vol 20 (4) ◽  
pp. 464-483 ◽  
Author(s):  
Donald G. Leckie
Keyword(s):  
Remote Sensing ◽  
Forest Management ◽  
Damage Assessment ◽  
Forest Type ◽  
New Technology ◽  
Remote Sensing Data ◽  
Forest Damage ◽  
Remote Sensing Technology ◽  
Sensing Technology ◽  
Remote Sensing Techniques

Canadian forest management has had a long history of developing and implementing remote sensing technology and is a major user of remote sensing. Despite difficulties in developing and implementing new digital remote sensing techniques, several key developments in Canadian forest management and in remote sensing and computer technology make the development and implementation of new remote sensing techniques at this time feasible and appropriate. Integration of different remote sensing technologies, remote sensing data with other information sources through geographic information systems, and remote sensing interpretations with forest management systems and practices are critical. Current capabilities and new advances in remote sensing technology for forest survey (excluding forest damage assessment) are discussed. Satellite imagery is a cost-effective tool for broad forest type mapping. New satellite systems improve this capability, but their major impact will be in inventories for new clear-cut and burned areas. Advances in linear array imager technology and lidar systems may lead to development of an end to end inventory mapping system. This system would provide an alternative to aerial photography and current mapping methods and could revolutionize the way forests are inventoried. Imaging spectrometry is a new technology with applications in damage assessment, but as yet has limited potential for assisting in other forest surveys. Spaceborne imaging radar systems are being developed for the 1990s. These systems can produce imagery under cloudy conditions. Their major impact on forestry will be to provide an alternative to visible-infrared satellite data for inventory update.

scholarly journals Application of Remote Sensing, GIS, and GPS Technology on Environment and Earth's Natural Resources Management An Introduction

2007 ◽  
Vol 6 (1) ◽  
pp. 96-117
Author(s):  
N. Nandini ◽  
Aboud S. Jumbe ◽  
Sucharita Tandon ◽  
Sunita N.
Keyword(s):  
Remote Sensing ◽  
Natural Resources ◽  
Satellite Data ◽  
Remote Sensing Data ◽  
Crop Monitoring ◽  
Sensing Data ◽  
Data Generator ◽  
Information Updates ◽  
Thematic Information ◽  
Meteorological Satellite

Remote sensing data have been used to derive thematic information of various natural resources and environment.The type and level of information extracted depends on the expertise of the analyst and what he/she is looking for in the data.An application in remote sensing is the practical use to which a series of aerial satellite images are put. The application of remote sensing or earth observation techniques to atmospheric, Earth and environmental sciences can vary according to the final user's requirements.The utilization of remote sensing data can be broadly classified into three categories as a baseline data generator for a variety of environmental resources; as a tool to monitor change detection, Environmental monitoring, and for mapping purposes. Different environmental applications require different frequencies of information updates for monitoring to be effective. Environment phenomena such as weather systems, natural hazards, and other rarely extreme events such as tsunamis; pollution or oceanographic events are very dynamic and rapidly develop over minutes and hours. Therefore for satellite data to be useful in their analysis imaging frequency and data delivery has to be atleast several times a day. At present only low spatial resolution meteorological satellite data can meet this need. Other applications such as crop monitoring require better spatial detail but rates of change occur only over a matter of weeks and therefore image updates need not be more frequent than weekly or monthly. This data can be processed, refined, and managed with the use of advanced tools such as Geographic Information System(GIS) and Geographic Positioning System(GPS).

Satellite remote sensing in the policy sphere

2019 ◽  
pp. 133-147
Author(s):  
Nathalie Pettorelli
Keyword(s):  
Remote Sensing ◽  
Natural Resources ◽  
Satellite Remote Sensing ◽  
Natural Capital ◽  
Remote Sensing Data ◽  
Resource Monitoring ◽  
Biodiversity Indicators ◽  
Sensing Technology ◽  
Essential Biodiversity Variables ◽  
Natural Resource Monitoring

This chapter focuses on the interface between satellite remote sensing and policy relevant to the management of natural resources, looking at ways for this technology to support decision making at the national to international scale. First, it briefly introduces (1) the main international conventions that are relevant to the management of natural resources and that could easily benefit from an increased consideration for satellite remote sensing technology, and (2) the main platforms facilitating the integration of satellite remote sensing data at the convention level. Second, it introduces the most popular conceptual frameworks that are being considered to help coordinate and structure natural resource monitoring efforts worldwide, namely the essential biodiversity variables framework, the biodiversity indicators framework, the ecosystem services framework, and the natural capital accounting framework. The final part highlights current challenges and lists a series of possible ways forward.

scholarly journals Remote Sensing Imagery Sensors and Image Interpretation

2021 ◽  
Vol 9 (9) ◽  
pp. 606-607
Author(s):  
Smriti Khare
Keyword(s):  
Remote Sensing ◽  
Image Interpretation ◽  
Remote Sensing Data ◽  
Basic Feature ◽  
Geographical Information ◽  
Earth Remote Sensing ◽  
Sensing Data ◽  
Remote Sensing Technology ◽  
The Earth ◽  
Sensing Technology

Abstract: Remote sensing a universal term that represents the activity of gaining data of an object with a sensor that is genuinely away from the item from an aircraft or satellite. Special cameras are used to gather remotely sensed picture which help the analyst to sense the things about the earth. Remote sensing makes it probable to assemble data of risky or unapproachable zones. Remote sensing data allows researchers to examine the biosphere's biotic and abiotic segments. Remote sensing is used in various fields to acquire the data which is widely used in Geographical Information System. Image interpretation is most basic feature of remote sensing technology. Image interpretation is a process of recognizing the images and collect information for multiple uses. The photographs are usually taken by satellite or aircrafts. Keywords: Image interpretation, image interpretation devices, sensor, remote sensing, data analysis.

scholarly journals VEGETATION MONITORING BY REMOTE SENSING TECHNOLOGY FOR UNINHABITED ISLANDS OF THE XISHA ISLANDS

2018 ◽  
Vol XLII-3 ◽  
pp. 853-856
Author(s):  
L. Li ◽  
Y. Guo ◽  
X. Wu
Keyword(s):  
Remote Sensing ◽  
Vegetation Change ◽  
Remote Sensing Data ◽  
Vegetation Monitoring ◽  
Xisha Islands ◽  
Remote Sensing Technology ◽  
Sensing Technology ◽  
Tropical Coral ◽  
South Sea ◽  
Stable Growth

The Xisha islands are tropical coral islands in the south sea of China, with special ecological environment. As far away from the inland, they are more sensitive to climate change than inland, and are looked as the window to reflect global environment changes. Since Sansha city established, some of islands were developed. The uninhabited islands are decreasing. To discover the changes of uninhabited islands become more impending. In order to find out the natural status of uninhabited islands, monitoring four years vegetation change of 2002, 2010, 2013 and 2016. In addition, monitoring the typical uninhabited island and sandbar vegetation by making the most of existed high resolution remote sensing data, nine years from 2002 to 2013 and six months in 2012. The results show that the sandbars are in stable growth stage, especially after 2010, the vegetation start appeared. Meanwhile, analysis the vegetation variation of the uninhabited islands and sandbars.

scholarly journals Indices Extraction from Multitemporal Remote Sensing Data for Mapping Urban Built-Up

2021 ◽  
Vol 887 (1) ◽  
pp. 012004
Author(s):  
A. K. Hayati ◽  
Y.F. Hestrio ◽  
N. Cendiana ◽  
K. Kustiyo
Keyword(s):  
Remote Sensing ◽  
Supervised Classification ◽  
Remote Sensing Data ◽  
Landsat 8 ◽  
Sensing Data ◽  
Remote Sensing Technology ◽  
Sensing Technology ◽  
Multitemporal Remote Sensing ◽  
Multitemporal Data

Abstract Remote sensing data analysis in the cloudy area is still a challenging process. Fortunately, remote sensing technology is fast growing. As a result, multitemporal data could be used to overcome the problem of the cloudy area. Using multitemporal data is a common approach to address the cloud problem. However, most methods only use two data, one as the main data and the other as complementary of the cloudy area. In this paper, a method to harness multitemporal remote sensing data for automatically extracting some indices is proposed. In this method, the process of extracting the indices is done without having to mask the cloud. Those indices could be further used for many applications such as the classification of urban built-up. Landsat-8 data that is acquired during 2019 are stacked, therefore each pixel at the same position creates a list. From each list, indices are extracted. In this study, NDVI, NDBI, and NDWI are used to mapping built-up areas. Furthermore, extracted indices are divided into four categories by their value (maximum, quantile 75, median, and mean). Those indices are then combined into a simple formula to mapping built-up to see which produces better accuracy. The Pleiades as high-resolution remote sensing data is used to assist supervised classification for assessment. In this study, the combination of mean NDBI, maximum NDVI, and mean NDWI result highest Kappa coefficient of 0.771.

scholarly journals Dynamic monitoring algorithm of natural resources in scenic spots based on MODIS Remote Sensing technology

2021 ◽  
Vol 25 (1) ◽  
pp. 57-64
Author(s):  
Maolin Li
Keyword(s):  
Remote Sensing ◽  
Natural Resources ◽  
Atmospheric Correction ◽  
Least Square Method ◽  
Least Square ◽  
Dynamic Monitoring ◽  
Remote Sensing Images ◽  
Remote Sensing Technology ◽  
Sensing Technology ◽  
Monitoring Algorithm

A dynamic monitoring algorithm of natural resources in scenic spots based on MODIS remote sensing technology is proposed to improve natural resources monitoring accuracy in scenic spots. The remote sensing images of scenic spots obtained by MODIS were preprocessed by TM image processing, atmospheric correction, and other technologies to get high-precision remote sensing images. The remote sensing images of scenic spots were segmented by the multi-scale segmentation method, and then the hierarchical supervision classification method was used. The change points of natural resources were extracted. The resource changes and independent variables of scenic spots were analyzed based on the least square method to realize the dynamic monitoring of natural resources in scenic locations. The experimental results show that the technique can accurately monitor the dynamic changes of forest resources and water resources in scenic spots, and the monitoring results have high accuracy.

Monitoring Water Resource in Taiyuan, China Using HJ-1B Imagery

2011 ◽  
Vol 356-360 ◽  
pp. 2892-2896
Author(s):  
Yan Chao Wang ◽  
Ji Long Zhang ◽  
Zhi Bin Wang ◽  
Jian Sheng Yang
Keyword(s):  
Remote Sensing ◽  
Water Resources ◽  
Remote Sensing Data ◽  
Water Area ◽  
Shanxi Province ◽  
Sensing Data ◽  
Monitoring Well ◽  
Remote Sensing Technology ◽  
Sensing Technology ◽  
Segmentation Threshold

Remote sensing technology can be used to quickly extract macro information of the study area, and its advantages in monitoring water resources have become increasingly evident. In this study, Fenhe 2nd reservoir and Jinyang Lake in Taiyuan，Shanxi Province were examined using the remote sensing data obtained from HJ-1B on May 6, 2010. Water area of Fenhe 2nd reservoir was extracted using NDWI and improved segmentation threshold. The distribution of eutrophication and phytoplankton in Jinyang Lake were analyzed using NDPI and a profile map of phytoplankton was produced. Results show that spatial and spectral resolution of HJ-1B can meet the requirements of water resources monitoring well, which are conducive for further promotion and application of HJ-1B remote sensing data.

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