Download or read book Using Multi temporal Landsat Thematic Mapper Data to Map Forest Cover types in New Hampshire written by James Schriever and published by . This book was released on 1992 with total page 166 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 Applying Spatial Autocorrelation Analysis to Evaluate Error in New England Forest Cover Type Maps Derived from Landsat Thematic Mapper Data written by Scott A. Pugh and published by . This book was released on 1997 with total page 458 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Forest Density Mapping in the Lower 48 States written by Zhiliang Zhu 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 Earth Resources written by and published by . This book was released on 1977 with total page 852 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book National Conference on Environmental Problem Solving with Geographic Information Systems written by and published by . This book was released on 1995 with total page 344 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Mapping Forest Communities in the Hudson River Valley of New York State Using Multi temporal Landsat TM Imagery written by Jennie Lynne Braden and published by . This book was released on 2002 with total page 258 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Mapping Forest Changes Using Multi temporal Remote Sensing Images written by Yanlei Chen and published by . This book was released on 2014 with total page 104 pages. Available in PDF, EPUB and Kindle. Book excerpt: We developed a semi-automatic algorithm named Berkeley Indices Trajectory Extractor (BITE) to detect forest disturbances, especially slow-onset disturbances such as insect mortality, from time series of Landsat 5 Thematic Mapper (TM) images. BITE is a streamlined process that features trajectory extraction and interpretation of multiple spectral indices followed by an integration of all indices. The algorithm was tested over Grand County in Colorado, located in the Southern Rocky Mountains Ecoregion, where forests dominated by lodgepole pine have been under mountain pine beetle attack since 2000. We produced a disturbance map using BITE with an identification accuracy of 94.7% assessed from 602 validation sample pixels. The algorithm shows its robustness in deriving forest disturbance type and timing with the presence of different levels of atmospheric conditions, noises, pixel misregistration and residual cloud/snow cover in the imagery. Outputs of the BITE algorithm could be used in studies designed to increase understanding of the mechanisms of mountain pine beetle dispersal and tree mortality, as well as other types of forest disturbances. Large remote sensing datasets, that either cover large areas or have high spatial resolution, are often a burden for information mining for scientific studies. Here, we present an approach that conducts clustering after gray-level vector reduction. In this manner, the speed of clustering can be considerably improved. The approach features applying eigenspace transformation to the dataset followed by compressing the data in the eigenspace and storing them in coded matrices and vectors. The clustering process takes advantage of the reduced size of the compressed data and thus reduces computational complexity. We name this approach Clustering Based on Eigen Space Transformation (CBEST). In our experiment with a subscene of Landsat Thematic Mapper (TM) imagery, CBEST was found to be able to improve speed considerably over conventional K-means as the volume of data to be clustered increases. We assessed information loss and several other factors. In addition, we evaluated the effectiveness of CBEST in mapping land cover/use with the same image that was acquired over Guangzhou City, South China and an AVIRIS hyperspectral image over Cappocanoe County, Indiana. Using reference data we assessed the accuracies for both CBEST and conventional K-means and we found that the CBEST was not negatively affected by information loss during compression in practice. We then applied CBEST in mapping the forest change from 1986-2011 for the entire state of California, USA with over 400 Landsat TM images. We discussed potential applications of the fast clustering algorithm in dealing with large datasets in remote sensing studies. We present an efficient approach for a practice of large-area mapping of forest changes based on the Clustering Based on Eigen Space Transformation (CBEST) algorithm using remote sensing. By analyzing 450 Landsat Thematic Mapper (TM) satellite images from 1986 to 2011 with a five-year interval covering the entire state of California, USA, we derived a forest change type map, a forest loss map and a forest gain map. Although California has 99.6 million acres land area in total and the spatial resolution of Landsat TM is 30m, the computing time of the task took only 10 hours in a computer with an Intel 2.8 Ghz i5 CPU and 8 Gigabytes RAM. The overall accuracy of the forest cover in year 2011 was reported as 92.9% " 1.6%. We found that the estimated forest area changed from 28.20 " 1.98 million acres to 28.05 " 1.98 million acres from 1986-2011. In particular, our rough estimate indicates that each year California's forest experienced loss of 92 thousand acres and recovery of 85 thousand acres, resulting in seven thousand acres forest loss per year. In addition, during 1986-2011, around 12% of the forestland experienced changes, in which the change was 4% each for deforestation, afforestation and deforestation then recovered respectively. We concluded that the forestland in California had been managed in a sustainable manner over the 25 years, since no significantly directional changes were observed. Our approach made a tighter estimate of the true canopy coverage such that 29% of land in California is forestland, comparing with the statistics of 33% and 40% made by previous studies that had lower spatial resolution and shorter temporal coverage.

Download or read book A Multitemporal Analysis of Land Cover in the Northern Forest of New England Using Landsat MSS Data written by Alison Bramley Miller and published by . This book was released on 1995 with total page 176 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Technical Guide for Change Detection Using Multi temporal Landsat TM Data written by and published by . This book was released on 1998 with total page 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 1989 with total page 956 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Google Earth Engine Applications written by Lalit Kumar and published by MDPI. This book was released on 2019-04-23 with total page 420 pages. Available in PDF, EPUB and Kindle. Book excerpt: In a rapidly changing world, there is an ever-increasing need to monitor the Earth’s resources and manage it sustainably for future generations. Earth observation from satellites is critical to provide information required for informed and timely decision making in this regard. Satellite-based earth observation has advanced rapidly over the last 50 years, and there is a plethora of satellite sensors imaging the Earth at finer spatial and spectral resolutions as well as high temporal resolutions. The amount of data available for any single location on the Earth is now at the petabyte-scale. An ever-increasing capacity and computing power is needed to handle such large datasets. The Google Earth Engine (GEE) is a cloud-based computing platform that was established by Google to support such data processing. This facility allows for the storage, processing and analysis of spatial data using centralized high-power computing resources, allowing scientists, researchers, hobbyists and anyone else interested in such fields to mine this data and understand the changes occurring on the Earth’s surface. This book presents research that applies the Google Earth Engine in mining, storing, retrieving and processing spatial data for a variety of applications that include vegetation monitoring, cropland mapping, ecosystem assessment, and gross primary productivity, among others. Datasets used range from coarse spatial resolution data, such as MODIS, to medium resolution datasets (Worldview -2), and the studies cover the entire globe at varying spatial and temporal scales.

Download or read book Surveying and Mapping written by and published by . This book was released on 1986 with total page 358 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Computer Analysis of Multitemporal Landsat Data for Mapping of Land use Forest Clearcuts and Mires Methodological Studies written by Leif Wastenson and published by . This book was released on 1981 with total page 14 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Classification Biomass Estimation and Carbon Dynamics of a Northern Forest Using SIR C X SAR Imagery written by Kathleen Mary Bergen and published by . This book was released on 1997 with total page 374 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Evaluation of Thematic Mapper Imagery for Forest Type Mapping and Its Use in a Computerized Hazard rating System written by Ann Louise MacLean and published by . This book was released on 1987 with total page 382 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book International Aerospace Abstracts written by and published by . This book was released on 1994 with total page 898 pages. Available in PDF, EPUB and Kindle. Book excerpt: