Download or read book Image Evaluation of LANDSAT Data for Monitoring Change in Forest Vigor written by John D. Rockie and published by . This book was released on 1985 with total page 201 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Monitoring Forest Canopy Alteration Around the World with Digital Analysis of Landsat Imagery written by D. L. Williams and published by . This book was released on 1979 with total page 56 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Forest Resource Change Detection Using High resolution Satellite Imagery for Monitoring and Effectiveness Evaluation written by Denis Collins and published by Nanaimo : Forest Service, British Columbia. This book was released on 2004 with total page 46 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Scientific and Technical Aerospace Reports written by and published by . This book was released on 1992 with total page 308 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book The Change Component in Multitemporal Landsat TM Images written by Pol Romain Coppin and published by . This book was released on 1991 with total page 378 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book The Use of LANDSAT Data in Forestry written by J. Cihlar and published by Harwood Academic Publishers. This book was released on 1986 with total page 278 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Continuous Change Detection and Classification of Land Cover Using All Available Landsat Data written by Zhe Zhu and published by . This book was released on 2013 with total page 322 pages. Available in PDF, EPUB and Kindle. Book excerpt: Abstract: Land cover mapping and monitoring has been widely recognized as important for understanding global change and in particular, human contributions.This research emphasizes the use of the time domain for mapping land cover and changes in land cover using satellite images. Unlike most prior methods that compare pairs or sets of images for identifying change, this research compares observations with model predictions. Moreover, instead of classifying satellite images directly, it uses coefficients from time series models as inputs for land cover mapping. The methods developed are capable of detecting many kinds of land cover change as they occur and providing land cover maps for any given time at high temporal frequency.One key processing step of the satellite images is the elimination of "noisy" observations due to clouds, cloud shadows, and snow. I developed a new algorithm called Fmask that processes each Landsat scene individually using an object-based method. For a globally distributed set of reference data, the overall cloud detection accuracy is 96%. A second step further improves cloud detection by using temporal information.The first application of the new methods based on time series analysis found change in forests in an area in Georgia and South Carolina. After the difference between observed and predicted reflectance exceeds a threshold three consecutive times a site is identified as forest disturbance. Accuracy assessment reveals that both the producers and users accuracies are higher than 95% in the spatial domain and approximately 94% in the temporal domain.The second application of this new approach extends the algorithm to include identification of a wide variety of land cover changes as well as land cover mapping. In this approach, the entire archive of Landsat imagery is analyzed to produce a comprehensive land cover history of the Boston region. The results are accurate for detecting change, with producers accuracy of 98% and users accuracies of 86% in the spatial domain and temporal accuracy of 80%. Overall, this research demonstrates the great potential for use of time series analysis of satellite images to monitor land cover change

Download or read book Advances in characterizing and monitoring land cover use and associated ecosystem changes using remote sensing data written by George Xian and published by Frontiers Media SA. This book was released on 2024-01-09 with total page 206 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Evaluation of Landsat Data Analysis for Forest Survey written by R. P. Mroczynski and published by . This book was released on 1980 with total page 54 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Earth Resources written by and published by . This book was released on 1983 with total page 758 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Forest Cover from Landsat Thematic Mapper Data for Use in the Catahoula Ranger District Geographic Information System written by David Lyle Evans and published by . This book was released on 1994 with total page 20 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Monitoring the Status of Mt Kenya Forest Using Multi temporal Landsat Data written by Lucy Wangeci Ndegwa and published by . This book was released on 2005 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: This study used three Landsat images acquired in 1976, 1987, and 2002, and ISODATA unsupervised classifications to map and quantify landcover changes on Mt. Kenya between 1976 and 2002. There were 194,707 ha, 150,812 ha, and 140,085 ha of forest in 1976, 1987, and 2002, respectively. Among the change detection techniques evaluated, the multitemporal PCA technique had the highest accuracy (86.9%) and indicated a 10.3% loss in forest between 1987 and 2002. The post classification comparison technique also resulted in high classification accuracy (80.3%), but failed to capture adequately loss in the bamboo forest. Other change detection techniques evaluated including KT wetness, KT greenness and SARVI2 gave misleading results, as they appeared to capture differences in forest growth vigor rather than actual biomass changes. Landscape metrics computed for the forests indicated higher fragmentation rates in the 1976-1987 period compared to the 1987-2002 period.

Download or read book Earth Resources written by and published by . This book was released on 1981 with total page 156 pages. Available in PDF, EPUB and Kindle. Book excerpt: A selection of annotated references to unclassified reports and journal articles that were introduced into the NASA scientific and technical information system and announced in Scientific and technical aerospace reports (STAR) and International Aerospace Abstracts (IAA).

Download or read book Assessing Local Expert Data Quality for Forest Monitoring written by E.B. Gebremeskel and published by . This book was released on 2014 with total page 51 pages. Available in PDF, EPUB and Kindle. Book excerpt: Recent advancement in spatial data collection technologies dramatically increases the contribution of ordinary people to collect and disseminate geospatial data. At the same time, there is an increasing general agreement that community based forest monitoring can play a crucial role in producing and sharing information about the condition of forest resources in time and space. Despite the advantages of the community based monitoring, there are also doubts and concerns that existed in the scientific community related to the quality of the data. Therefore, this research is aiming to assess the quality of forest monitoring activity data sets, which is collected by local experts in Kafa Biosphere Reserve in Ethiopia. The research was conducted to test the quality of local experts data for REDD+ mechanism to track the forest change and carbon emissions. In this research, we examines the quality of local experts data relative to the reference data sets of remotes sensing time series images of 2005 to 2012, GIS data sets, and ground based validation measurements. The main variables are date of forest disturbances, size of the forest disturbance, drivers information, location and coverage of forest disturbances. The spatial variables of the local experts data were assessed using the spatial data quality parameters whereas the temporal variables were compared through BFAST monitoring on Landsat time series images and visual interpretations on high resolution images of Spot and Rapid Eye. The results show that the local experts can perform and produce quality data comparable to validation measurements by experts. We found a regression coefficient value of 0.84 for area/size estimation and ~65% of correctly classification accuracy of drivers information of forest disturbances. Furthermore, the result confirms that local experts have a short time delay in detecting forest disturbances compared to high resolution remote sensing time series data of Spot 5-Rapid Eye satellite images than of Landsat imagery. Based up on the findings of this study, we suggests that the local expert data can enhance the quality of forest monitoring data of remote sensing particularly in detecting near real time forest disturbances.

Download or read book Improving Forest Monitoring Combining Temporal and Spatial Information to Enable for an Automated and Accurate Detection of Forest Cover Change written by A. Castro Gómez and published by . This book was released on 2015 with total page 59 pages. Available in PDF, EPUB and Kindle. Book excerpt: In the context of REDD+, the accurate identification of active forest change areas from remote sensing sensors is essential to monitor, report and verify tropical deforestation efficiently. Landsat imagery is considered the most viable option due to its high-resolution data, and extensive and free archive. However, the high level of noise (e.g. clouds or climatic disturbances) in Landsat data from tropical areas reduces the reliability of the detection of deforestation. Pre-processing is essential in order to detect deforestation reliably, but for Landsat no comprehensive methodology for cloud screening is available, and the correction of external disturbances remains to be addressed. The main objective is to improve the detection of deforestation from Landsat image time series by including information of the spatial neighbourhood of a pixel.

Download or read book Monitoring Forest Cover and Land Use Change in Forest Reserves Connecting Satellite Imagery to Anthropogenic Impacts written by and published by . This book was released on 2018 with total page 95 pages. Available in PDF, EPUB and Kindle. Book excerpt: Despite their protected status, forest reserves can be influenced by anthropogenic activities within and adjacent to reserve boundaries, resulting in environmental degradation and changes in forest cover. Long-term monitoring of environmental change within protected areas in a reliable and extensive manner is important given widespread, human-induced land-cover and land-use change. This study demonstrates the utility of optical satellite remotely sensed imagery and multi-temporal image analysis procedures for mapping and monitoring land cover and land use within cloud-prone and mountainous forest reserves and their environs in China and Ghana for the period of mid-1980s to 2018. The novel mapping and monitoring procedures yield extensive land-use dynamic information in a reliable manner by minimizing terrain-related illumination and cloud cover effects. Forest types and land-use are mapped in selected cloud-prone and mountainous forest reserves in China and Ghana to test the reliability of the optimized methods. By applying logical land-use transition rules and interpreting high spatial resolution satellite imagery, land-use changes and the anthropogenic activities associated with them are identified. Vegetation and land-use types are mapped with moderate to high classification accuracies (64 to 94%) for study areas in China and Ghana. For Fanjingshan National Nature Reserve in China, 12 km2 in land area is mapped as afforested bamboo and conifer lands associated with payment for ecosystem services programs, and over 25 km2 is mapped as new development during 1995-2016. Forest area decreased by 9% for the 76 study reserves and environs in southern Ghana between 2000 and 2018. Substantial land changes associated with built development and agricultural expansion are observed in reserve environs within both study areas. Other anthropogenic activities including mining and plantation activities are identified in southern Ghana reserves, while afforestation activities associated with payment for ecosystem programs were predominant adjacent to Fanjingshan in China. This study contributes to the land-cover and land-use mapping literature by developing and optimizing methods for extremely cloud prevalent and mountainous regions. A semi-automated mapping approach implemented on an open-access, user-friendly platform, similar to the workflow demonstrated in this study, increases the usability and transferability of such mapping techniques. Improved monitoring of other forested, mountainous, and cloud prevalent regions can benefit and inform protected area management and policy, long-term environmental change monitoring, and conservation effort assessment.

Download or read book Fusion of MODIS and Landsat Data to Allow Near Real time Monitoring of Land Surface Change written by Qinchuan Xin and published by . This book was released on 2012 with total page 260 pages. Available in PDF, EPUB and Kindle. Book excerpt: Abstract: A new methodology for fusion of MODIS and Landsat data improves monitoring of land surface change and snow mapping. This fusion method is based on prediction of MODIS data using a time-series of Landsat data. An underlying hypothesis is that the predicted MODIS images will form a more stable basis for comparison with new MODIS images than previous MODIS images. Correlations between predicted and observed MODIS images are higher than for successive days of MODIS data, confirming our hypothesis. Differences in the spectral signatures between predicted and real MODIS images become the "signal" used detect land surface change. Tests of the fusion method to detect forest clearing show producer's and user's accuracies of 86% and 85%, respectively. Cleared patches of forest as small as 5-6 ha in size can be detected, a considerable improvement over current published results. Additionally, the fusion method can be used to map snow cover on a daily basis and is more accurate than current operational MODIS snow products. The encouraging results indicate that the fusion method holds promise for improving monitoring of land surface change in near real-time.