scholarly journals Vegetation Height Estimation using Satellite Remote Sensing in Peat Land of Central Kalimantan

2021 ◽  
Vol 6 (1) ◽  
pp. 024-034
Author(s):  
Atriyon Julzarika ◽  
Harintaka Harintaka ◽  
Tatik Kartika
Keyword(s):  
Remote Sensing ◽  
Spatial Information ◽  
Geoid Undulation ◽  
Height Estimation ◽  
Central Kalimantan ◽  
Vegetation Height ◽  
Accuracy Test ◽  
Sensing Technology ◽  
The Difference ◽  
Difference Test

Vegetation height is an important parameter in monitoring peatlands. Vegetation height can be estimated using remote sensing. Vegetation height can be estimated by utilizing DSM and DTM. The data that can be used are LiDAR, X-SAR, and SRTM C. In this study, LiDAR data is used for DSM2018 and DTM2018 extraction. The purpose of this research is to detect the vegetation height in Central Kalimantan peatlands using remote sensing technology. The research location is in Bakengbongkei, Kalampangan, Central Kalimantan. The integration of X-SAR and SRTM C is used for DSM2000 and DTM2000 extraction. DSM2000, DTM2000, DSM2018, and DTM2018 performed height error correction with tolerance of 1.96? (95%). Then do the geoid undulation correction to EGM2008. The results obtained are DSM and DTM with a similar height reference field. If it meets these conditions it can be calculated the vegetation height estimation. Vegetation height can be obtained using the Differential DEM method. The Changing in vegetation height from 2000 to 2018 can be estimated from the difference in vegetation height from 2000 to vegetation height in 2018. Results of spatial information on vegetation height and its changes need to be tested for the accuracy. This accuracy-test includes a cross section test, height difference test, and comparison with measurements of vegetation height in the field. The results of this research can be used to monitor the changing the vegetation height in peatlands.

scholarly journals Teaching of Remote Sensing Technology for Landscape Architecture in the Context of Spatial Information Technology

2021 ◽  
Vol 16 (15) ◽  
pp. 125
Author(s):  
Xueling Zhang ◽  
Dayu Zhang
Keyword(s):  
Remote Sensing ◽  
Information Technology ◽  
Information Integration ◽  
Landscape Architecture ◽  
Spatial Information ◽  
Sensing Technology ◽  
Application Potential ◽  
Professional Teaching ◽  
Spatial Information Technology ◽  
Digital Landscape

The research of digital landscape architecture springs up in recent years. The emerging digital technology provides a rational and objective method to mine and quantify the endogenous laws of landscape architecture. Remote sensing (RS) technology has become a new growth point in the current research and design of landscape spatial information. To develop the professional teaching of landscape architecture, it is important to fully integrate the RS technology into the teaching system of spatial information technology, carry out systematic spatial information quantification and research-based teaching of landscape architecture, and collaboratively promote the teaching of landscape architecture design. This paper firstly analyzes the integration and application potential of RS technology into landscape architecture. Considering the demand and trend of information-based teaching of landscape architecture, the authors integrated the relevant technologies into an RS teaching platform for landscape architecture, and summarized an application model of RS technology in the teaching of landscape architecture theories and practices. Moreover, a landscape spatial information chain, which is question-oriented, task-driven, and exploration-based, was constructed to promote the synergistic development between the students’ research and practice ability under spatial information integration.

scholarly journals THE EFFECT OF DIFFERENT ATMOSPHERIC CORRECTIONS ON BATHYMETRY EXTRACTION USING LANDSAT 8 SATELLITE IMAGERY

2017 ◽  
Vol 12 (1) ◽  
pp. 13 ◽  
Author(s):  
Kuncoro Teguh Setiawan ◽  
Yennie Marini ◽  
Johannes Manalu ◽  
Syarif Budhiman
Keyword(s):  
Remote Sensing ◽  
Satellite Image ◽  
Atmospheric Correction ◽  
Remote Sensing Data ◽  
Image Data ◽  
Landsat 8 ◽  
Calculation Error ◽  
Sensing Technology ◽  
The Difference ◽  
Landsat Satellite

Remote sensing technology can be used to obtain information bathymetry. Bathymetric information plays an important role for fisheries, hydrographic and navigation safety. Bathymetric information derived from remote sensing data is highly dependent on the quality of satellite data use and processing. One of the processing to be done is the atmospheric correction process. The data used in this study is Landsat 8 image obtained on June 19, 2013. The purpose of this study was to determine the effect of different atmospheric correction on bathymetric information extraction from Landsat satellite image data 8. The atmospheric correction methods applied were the minimum radiant, Dark Pixels and ATCOR. Bathymetry extraction result of Landsat 8 uses a third method of atmospheric correction is difficult to distinguish which one is best. The calculation of the difference extraction results was determined from regression models and correlation coefficient value calculation error is generated.

scholarly journals On the Use of Low-Cost RGB-D Sensors for Autonomous Pothole Detection with Spatial Fuzzy c-Means Segmentation

2020 ◽  
Author(s):  
Yashon Ombado Ouma
Keyword(s):  
Remote Sensing ◽  
Spatial Information ◽  
Low Cost ◽  
Complex Structure ◽  
Pavement Distress ◽  
Fuzzy C Means ◽  
Sensing Technology ◽  
Efficiency And Effectiveness ◽  
The Individual ◽  
Pothole Detection

The automated detection of pavement distress from remote sensing imagery is a promising but challenging task due to the complex structure of pavement surfaces, in addition to the intensity of non-uniformity, and the presence of artifacts and noise. Even though imaging and sensing systems such as high-resolution RGB cameras, stereovision imaging, LiDAR and terrestrial laser scanning can now be combined to collect pavement condition data, the data obtained by these sensors are expensive and require specially equipped vehicles and processing. This hinders the utilization of the potential efficiency and effectiveness of such sensor systems. This chapter presents the potentials of the use of the Kinect v2.0 RGB-D sensor, as a low-cost approach for the efficient and accurate pothole detection on asphalt pavements. By using spatial fuzzy c-means (SFCM) clustering, so as to incorporate the pothole neighborhood spatial information into the membership function for clustering, the RGB data are segmented into pothole and non-pothole objects. The results demonstrate the advantage of complementary processing of low-cost multisensor data, through channeling data streams and linking data processing according to the merits of the individual sensors, for autonomous cost-effective assessment of road-surface conditions using remote sensing technology.

Remote Sensing in Mineral Exploration

SEG Discovery ◽  
2004 ◽  
pp. 1-14
Author(s):  
Richard Bedell
Keyword(s):  
Remote Sensing ◽  
Mineral Exploration ◽  
Ore Deposit ◽  
Remote Sensing Technology ◽  
Sensing Systems ◽  
Sensing Technology ◽  
Reflected Light ◽  
Sensing Platforms ◽  
Remote Sensing Systems ◽  
The Difference

ABSTRACT The proliferation of remote sensing platforms has resulted in unprecedented opportunities for ore deposit vectoring. Importantly, remote sensing technology is now beyond the vague identifıcation of alteration, and can accurately map specifıc minerals and directly contribute to the understanding of ore systems. Remote sensing is making discoveries of new alteration zones within classic and previously well mapped ore systems, as well as outlining their geometry and mineralogy. Confıning this review to the geologically important reflected-light remote sensing systems, there are four main categories of sensors readily available to economic geologists, including the following: (1) submeter resolution panchromatic satellites that offer little spectral information but provide base maps; (2) multispectral Landsat satellites that can map iron and clay alteration; (3) the new ASTER satellite that can map important alteration groups and some specifıc minerals; and (4) hyperspectral airborne scanners that can provide maps of specifıc mineral species important to detailed alteration mapping. At the core of comprehending this plethora of technology is the difference between spectral and spatial resolution. This review will provide an understanding of the more fundamental aspects of remote sensing systems that will help fıeld geologists to interact better with and leverage this rapidly evolving technology.

scholarly journals TCANet for Domain Adaptation of Hyperspectral Images

2019 ◽  
Vol 11 (19) ◽  
pp. 2289 ◽  
Author(s):  
Alberto S. S. Garea ◽  
Dora B. Heras ◽  
Francisco Argüello
Keyword(s):  
Remote Sensing ◽  
Input Data ◽  
Spatial Information ◽  
Hyperspectral Image ◽  
Domain Adaptation ◽  
Computational Cost ◽  
Hyperspectral Images ◽  
Classification Problems ◽  
Output Stage ◽  
The Difference

The use of Convolutional Neural Networks (CNNs) to solve Domain Adaptation (DA) image classification problems in the context of remote sensing has proven to provide good results but at high computational cost. To avoid this problem, a deep learning network for DA in remote sensing hyperspectral images called TCANet is proposed. As a standard CNN, TCANet consists of several stages built based on convolutional filters that operate on patches of the hyperspectral image. Unlike the former, the coefficients of the filter are obtained through Transfer Component Analysis (TCA). This approach has two advantages: firstly, TCANet does not require training based on backpropagation, since TCA is itself a learning method that obtains the filter coefficients directly from the input data. Second, DA is performed on the fly since TCA, in addition to performing dimensional reduction, obtains components that minimize the difference in distributions of data in the different domains corresponding to the source and target images. To build an operating scheme, TCANet includes an initial stage that exploits the spatial information by providing patches around each sample as input data to the network. An output stage performing feature extraction that introduces sufficient invariance and robustness in the final features is also included. Since TCA is sensitive to normalization, to reduce the difference between source and target domains, a previous unsupervised domain shift minimization algorithm consisting of applying conditional correlation alignment (CCA) is conditionally applied. The results of a classification scheme based on CCA and TCANet show that the DA technique proposed outperforms other more complex DA techniques.

scholarly journals Integration of Remote Sensing Technology Using Sentinel-2A Satellite images For Fertilization and Water Pollution Analysis in Estuaries Inlet of Semarang Eastern Flood Canal

2018 ◽  
Vol 31 ◽  
pp. 12008
Author(s):  
Sawitri Subiyanto ◽  
Zainab Ramadhanis ◽  
Aditya Hafidh Baktiar
Keyword(s):  
Remote Sensing ◽  
Water Quality ◽  
Chlorophyll A ◽  
Satellite Images ◽  
Spectral Characteristics ◽  
River System ◽  
Remote Sensing Technology ◽  
Accuracy Test ◽  
Sensing Technology ◽  
Sentinel 2A

One of the waters that has been contaminated by industrial waste and domestic waste is the waters in estuaries inlet of Semarang Eastern Flood Canal which is the estuary of the river system, which passes through the eastern city of Semarang which is dense with residential and industrial. So it is necessary to have information about the assessment of water quality in Estuaries Inlet of Semarang Eastern Flood Canal. Remote sensing technology can analyze the results of recording the spectral characteristics of water with water quality parameters. One of the parameters for assessing water quality is Chlorophyll-a and Total Suspended Solid, can be estimated through remote sensing technology using multispectral Sentinel-2A Satellite images. In this research there are 3 algorithms that will be used in determining the content of chlorophyll a, and for determining TSS. Image accuracy test is done to find out how far the image can give information about Chlorophyll-a and TSS in the waters. The results of the image accuracy test will be compared with the value of chlorophyll-a and TSS that have been tested through laboratory analysis. The result of this research is the distribution map of chlorophyll-a and TSS content in the waters.

Hyperspectral Remote Sensing Technology (HRST) program

1997 ◽  
Author(s):  
Tom Wilson ◽  
Rebecca Baugh ◽  
Ron Contillo ◽  
Tom Wilson ◽  
Rebecca Baugh ◽  
...  
Keyword(s):  
Remote Sensing ◽  
Hyperspectral Remote Sensing ◽  
Remote Sensing Technology ◽  
Sensing Technology

Application of remote sensing technology to the relation of submarine pipelines and coastal morphology

1995 ◽  
Vol 32 (2) ◽  
pp. 77-83
Author(s):  
Y. Yüksel ◽  
D. Maktav ◽  
S. Kapdasli
Keyword(s):  
Remote Sensing ◽  
Sediment Transport ◽  
Surf Zone ◽  
Hydrodynamic Forces ◽  
Construction Site ◽  
Coastal Morphology ◽  
Remote Sensing Technology ◽  
Sensing Technology ◽  
Sea Bed

Submarine pipelines must be designed to resist wave and current induced hydrodynamic forces especially in and near the surf zone. They are buried as protection against forces in the surf zone, however this procedure is not always feasible particularly on a movable sea bed. For this reason the characteristics of the sediment transport on the construction site of beaches should be investigated. In this investigation, the application of the remote sensing method is introduced in order to determine and observe the coastal morphology, so that submarine pipelines may be protected against undesirable seabed movement.

POTENSI HASIL JAGUNG MANIS (Zea mays saccharata, Sturt) DENGAN PEMBERIAN PAKET TEKNOLOGI PUPUK DAN ZAT PENGATUR TUMBUH

Jurnal BiBieT ◽  
2017 ◽  
Vol 2 (1) ◽  
pp. 37
Author(s):  
Surtinah Surtinah
Keyword(s):  
Zea Mays ◽  
Sugar Content ◽  
Environmental Design ◽  
Randomized Design ◽  
The Difference ◽  
Difference Test ◽  
Treatment Design ◽  
Fertilizer Technology

<p>Tujuan penelitian adalah untuk mengetahui paket teknologi yang memberikan produksi jagung manis varietas Master Sweet yang terbaik.  Rancangan Perlakuan yang diuji adalah paket teknologi pupuk Bio Extrim dan ZPT Hormax yang terdiri dari delapan taraf, dan rancangan lingkungan yang digunakan adalah rancangan acak lengkap dengan uji beda rata-rata perlakuan DMRT pada p 0.5.    Hasil penelitian memperlihatkan bahwa paket teknologi dengan pemberian Hormax tanpa Bio Extrim menghasilkan kadar gula yang terbaik.</p><p><strong><em> </em></strong></p><p><em>The aim of the research was to find out the technology package that gives the best Sweet Sweet varieties production. The treatment design tested was the Bio Extreme fertilizer technology package and the Hormax ZPT consisting of eight levels, and the environmental design used was a complete randomized design with the difference test of the average DMRT treatment at p 0.5. The results showed that the technology package with Hormax without Bio Extreme resulted in the best sugar content</em></p>

scholarly journals Combined Multi-Time Series SAR Imagery and InSAR Technology for Rice Identification in Cloudy Regions

2021 ◽  
Vol 11 (15) ◽  
pp. 6923
Author(s):  
Rui Zhang ◽  
Zhanzhong Tang ◽  
Dong Luo ◽  
Hongxia Luo ◽  
Shucheng You ◽  
...  
Keyword(s):  
Remote Sensing ◽  
Time Series ◽  
Identification Accuracy ◽  
Optical Remote Sensing ◽  
Sar Image ◽  
Single Time ◽  
Growing Period ◽  
Sensing Technology ◽  
Sar Imagery ◽  
Cloudy Region

The use of remote sensing technology to monitor farmland is currently the mainstream method for crop research. However, in cloudy and misty regions, the use of optical remote sensing image is limited. Synthetic aperture radar (SAR) technology has many advantages, including high resolution, multi-mode, and multi-polarization. Moreover, it can penetrate clouds and mists, can be used for all-weather and all-time Earth observation, and is sensitive to the shape of ground objects. Therefore, it is widely used in agricultural monitoring. In this study, the polarization backscattering coefficient on time-series SAR images during the rice-growing period was analyzed. The rice identification results and accuracy of InSAR technology were compared with those of three schemes (single-time-phase SAR, multi-time-phase SAR, and combination of multi-time-phase SAR and InSAR). Results show that VV and VH polarization coherence coefficients can well distinguish artificial buildings. In particular, VV polarization coherence coefficients can well distinguish rice from water and vegetation in August and September, whereas VH polarization coherence coefficients can well distinguish rice from water and vegetation in August and October. The rice identification accuracy of single-time series Sentinel-1 SAR image (78%) is lower than that of multi-time series SAR image combined with InSAR technology (81%). In this study, Guanghan City, a cloudy region, was used as the study site, and a good verification result was obtained.

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