Dr. Projo Danoedoro Profile

Dr. Projo Danoedoro

Senior lecturer in Remote Sensing at Univ Gadjah Mada

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Publications (15)

Proceedings Article | 29 January 2024 Paper

Landscape fragmentation analysis in Riau Province based on Sentinel-2A and SRTM imagery

Fitria Alfani, Projo Danoedoro

Proceedings Volume 12977, 129770B (2024) https://doi.org/10.1117/12.3009775

KEYWORDS: Remote sensing, Windows, Image processing, Land cover, Ecology, Data processing, Spatial resolution

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Proceedings Article | 29 January 2024 Paper

Understanding the influence of different sample sizes and sample techniques on accuracy assessment of land cover mapping: case study of Salatiga city, Indonesia

William Krista Mahendra, Projo Danoedoro

Proceedings Volume 12977, 129770E (2024) https://doi.org/10.1117/12.3009445

KEYWORDS: Land cover, Accuracy assessment, Visualization, Spatial resolution, Image classification, Associative arrays, Remote sensing, Satellites, Satellite imaging, Education and training

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Proceedings Article | 29 January 2024 Paper

Gully erosion mapping based on remote sensing data

Alfiatun Nur Khasanah, Projo Danoedoro, Muhammad Anggri Setiawan

Proceedings Volume 12977, 129771F (2024) https://doi.org/10.1117/12.3009755

KEYWORDS: Modeling, Vegetation, Data modeling, Remote sensing, Machine learning, Random forests, Associative arrays, Roads, Agriculture, Systems modeling

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Proceedings Article | 22 December 2021 Paper

The effect of atmospheric and topographic corrections on the vegetation density mapping using several vegetation indices: a case study in Arjuno-Welirang volcanoes, East Java

Huwaida Nur Salsabila, Projo Danoedoro

Proceedings Volume 12082, 120820S (2021) https://doi.org/10.1117/12.2621837

KEYWORDS: Vegetation, Near infrared, Earth observing sensors, Remote sensing, Landsat, Java

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Proceedings Article | 22 December 2021 Paper

Comparing several pixel-based classification methods for vegetation structural composition mapping using Sentinel 2A imagery in Salatiga area, Central Java

Haeydar Anggara Hadi, Projo Danoedoro

Proceedings Volume 12082, 120820T (2021) https://doi.org/10.1117/12.2621965

KEYWORDS: Vegetation, Image classification, Remote sensing, Image processing

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Proceedings Article | 24 December 2019 Paper

Comparing per-pixel and object-based classification results using two different land-cover/land-use classification schemes: a case study using Landsat-8 OLI imagery

Erisa A. Putri, Projo Danoedoro

Proceedings Volume 11372, 1137206 (2019) https://doi.org/10.1117/12.2541876

KEYWORDS: Image classification, Earth observing sensors, Image segmentation, Landsat, Spatial resolution, Accuracy assessment, Remote sensing, Satellites, Image analysis

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Proceedings Article | 24 December 2019 Paper

Developing interpretation methods for detailed categorisation-based land-cover/land-use mapping at 1:50,000 scale in Indonesia

Projo Danoedoro, Irvan Ananda, Yuniarsita Wulandari, Assyria Umela, Nila Ratnasari, Emil Rasyidi, Muhammad Pahlefi, Dyah Ramadanningrum, Inna Kulsum, Anwar Juniansah, Brada Tyas, Laila Rosalina, Dyah Arshinta Narmaningrum

Proceedings Volume 11372, 1137205 (2019) https://doi.org/10.1117/12.2541857

KEYWORDS: Vegetation, Earth observing sensors, Mining, Landsat, Visualization, Accuracy assessment, Image analysis, Image processing

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Proceedings Article | 24 December 2019 Paper

Paddy and non-paddy crops mapping using multi-temporal data of Sentinel-1A in part of Bantul Regency

Ruwanda Prasetya, Projo Danoedoro

Proceedings Volume 11372, 113720G (2019) https://doi.org/10.1117/12.2540635

KEYWORDS: Polarization, Synthetic aperture radar, Agriculture, Backscatter, Image classification, Sensors, Satellites

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Proceedings Article | 21 November 2019 Open Access

Correcting topographic effect on Landsat-8 images: an evaluation of using different DEMs in Indonesia

Deha Agus Umarhadi, Projo Danoedoro

Proceedings Volume 11311, 113110L (2019) https://doi.org/10.1117/12.2549109

KEYWORDS: Earth observing sensors, Landsat, Reflectivity, Vegetation, Statistical analysis, Spatial resolution, Visual analytics, Visualization, Sun, Data modeling

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Proceedings Article | 21 November 2019 Open Access

Development of land-cover spatial database using satellite imagery: lesson learned from southern part of Sumatera

Irvan Ananda, Assyria Umela, Nila Ratnasari, Desi Putri, Yuniarsita Wulandari, Projo Danoedoro

Proceedings Volume 11311, 113110V (2019) https://doi.org/10.1117/12.2548890

KEYWORDS: Earth observing sensors, Landsat, Databases, Standards development, Image processing, Accuracy assessment, Spatial resolution, Vegetation, Remote sensing, Satellite imaging

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Proceedings Article | 21 November 2019 Open Access

The effects of polynomial interpolation and resampling methods in geometric correction on the land-cover classification accuracy of Landsat-8 OLI imagery: a case study of Kulon Progo area, Yogyakarta

Muhammad Zayyanul Afwani, Projo Danoedoro

Proceedings Volume 11311, 113110T (2019) https://doi.org/10.1117/12.2548423

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Geometric correction is an important step in image pre-processing, because it determines the the positional accuracy of the data. However, the geometric correction also includes pixel values interpolation in their new position, so that it may change original values. This study objectives were (a) to provide information on the effect of geometric correction models on the accuracy of land-cover classification, especially using per-pixel classification with maximum likelihood algorithm; and (b) to assess the effect of image resampling methods on the accuracy of the multispectral classification results. This study made use of Landsat 8 OLI Level 1G imagery covering Kulon Progo Area, Yogyakarta, so that several ground control points (GCPs) were needed to suppress geometric errors. Non-systematic geometric correction was undertaken using first, second and third order polynomial transformations. After that, several resampling processes were applied to the geometrically corrected image, i.e. Nearest Neighbour, Bilinear and Cubic Convolution interpolations. It was found that the affine transformation using six GCPs distributed over the edges of the image, delivered an RMSE value of 0.355539. In addition, the second order polynomial with 10 GCPs scattered around the edges of the image gave an RMSE value of 0.178053. While the third order polynomial transformation with 17 GCPs that were evenly distributed in the image produced an RMSE value of 0.100343. The resampling process produced new images with new pixel values, which were then tested with respect to their classification accuracies based on maximum likelihood algorithm. Samples for accuracy assessment were taken using stratified random sampling strategy. Samples were taken in terms of polygons whose size was determined by considering the pixels’ displacement as the results of geometric corrections. This study also found that resampling with nearest neighbour interpolation using third order polynomial equation produced the best overall accuracy of 75.46%, with a Kappa of 0.7032.

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Proceedings Article | 21 November 2019 Open Access

Multitemporal analysis of vegetated land cover changes related to tin mining activity in Bangka Regency using Landsat imagery

Ningsih Tassri, Projo Danoedoro, Prima Widayani

Proceedings Volume 11311, 1131104 (2019) https://doi.org/10.1117/12.2548887

KEYWORDS: Mining, Tin, Earth observing sensors, Landsat, Image classification, Image processing, Remote sensing, Composites, Accuracy assessment, Minerals

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Proceedings Article | 21 November 2019 Open Access

Comparing land-cover maps accuracies generated from multispectral classification of Landsat-8 OLI dan Pleiades images using two different classification schemes

Erisa Ayu W. Putri, Projo Danoedoro, Nur Farda

Proceedings Volume 11311, 113110U (2019) https://doi.org/10.1117/12.2548888

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Proceedings Article | 10 October 2018 Paper

Comparison of scoring, matching, SMCE and geographically weighted regression In malaria vulnerability spatial modelling using satellite imagery: an Indonesian example

Prima Widayani, Projo Danoedoro

Proceedings Volume 10783, 107832H (2018) https://doi.org/10.1117/12.2325680

KEYWORDS: Remote sensing, Earth observing sensors, Satellite imaging, Satellites, Statistical analysis, Modeling, Environmental sensing, Data modeling, Java, Landsat

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Proceedings Article | 7 October 2011 Paper

Preliminary work of mangrove ecosystem carbon stock mapping in small island using remote sensing: above and below ground carbon stock mapping on medium resolution satellite image

Pramaditya Wicaksono, Projo Danoedoro, Hartono Hartono, Udo Nehren, Lars Ribbe

Proceedings Volume 8174, 81741B (2011) https://doi.org/10.1117/12.897926

KEYWORDS: Carbon, Vegetation, Remote sensing, Carbon sequestration, Radiometric corrections, Landsat, Ecosystems, Reflectivity, Error analysis, Earth observing sensors

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Showing 5 of 15 publications

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