Next Article in Journal
The UVSQ-SAT/INSPIRESat-5 CubeSat Mission: First In-Orbit Measurements of the Earth’s Outgoing Radiation
Previous Article in Journal
On the Use of Standardized Multi-Temporal Indices for Monitoring Disturbance and Ecosystem Moisture Stress across Multiple Earth Observation Systems in the Google Earth Engine
Article

Assessing Accuracy of Land Cover Change Maps Derived from Automated Digital Processing and Visual Interpretation in Tropical Forests in Indonesia

1
Remote Sensing Technology and Data Center, National Institute of Aeronautics and Space of Indonesia (LAPAN), Jakarta 13710, Indonesia
2
School of Ecosystem and Forest Sciences, Faculty of Science, The University of Melbourne, Creswick, VIC 3363, Australia
3
CSIRO Land and Water, Private Bag 10, Clayton South, VIC 3169, Australia
*
Author to whom correspondence should be addressed.
Academic Editor: Raymond L. Czaplewski
Remote Sens. 2021, 13(8), 1446; https://doi.org/10.3390/rs13081446
Received: 16 February 2021 / Revised: 3 April 2021 / Accepted: 6 April 2021 / Published: 8 April 2021
This study assessed the accuracy of land cover change (2000–2018) maps compiled from Landsat images with either automated digital processing or with visual interpretation for a tropical forest area in Indonesia. The accuracy assessment used a two-stage stratified random sampling involving a confusion matrix for assessing map accuracy and by estimating areas of land cover change classes and associated uncertainty. The reference data were high-resolution images from SPOT 6/7 and high-resolution images finer than 5 m obtained from Open Foris Collect Earth. Results showed that the map derived from automated digital processing had lower accuracy (overall accuracy 73–77%) compared to the map based on visual interpretation (overall accuracy 80–84%). The automated digital processing map error was in differentiating between native forest and plantation areas. While the visual interpretation map had a higher accuracy, it did not consistently differentiate between native forest and shrub areas. Future improvement of the digital map requires more accurate differentiation between forest and plantation to better support national forest monitoring systems for sustainable forest management. View Full-Text
Keywords: accuracy assessment; land cover change maps; automated digital processing; visual interpretation; two-stage stratified random sampling accuracy assessment; land cover change maps; automated digital processing; visual interpretation; two-stage stratified random sampling
Show Figures

Graphical abstract

MDPI and ACS Style

Sari, I.L.; Weston, C.J.; Newnham, G.J.; Volkova, L. Assessing Accuracy of Land Cover Change Maps Derived from Automated Digital Processing and Visual Interpretation in Tropical Forests in Indonesia. Remote Sens. 2021, 13, 1446. https://doi.org/10.3390/rs13081446

AMA Style

Sari IL, Weston CJ, Newnham GJ, Volkova L. Assessing Accuracy of Land Cover Change Maps Derived from Automated Digital Processing and Visual Interpretation in Tropical Forests in Indonesia. Remote Sensing. 2021; 13(8):1446. https://doi.org/10.3390/rs13081446

Chicago/Turabian Style

Sari, Inggit L., Christopher J. Weston, Glenn J. Newnham, and Liubov Volkova. 2021. "Assessing Accuracy of Land Cover Change Maps Derived from Automated Digital Processing and Visual Interpretation in Tropical Forests in Indonesia" Remote Sensing 13, no. 8: 1446. https://doi.org/10.3390/rs13081446

Find Other Styles
Note that from the first issue of 2016, MDPI journals use article numbers instead of page numbers. See further details here.

Article Access Map by Country/Region

1
Back to TopTop