3D Remote Sensing Applications in Forest Ecology: Composition, Structure and Function
Dear Colleagues, The composition, structure and function of forest ecosystems are the key features characterizing their ecological properties, and can thus be crucially shaped and changed by various biotic and abiotic factors on multiple spatial scales. The magnitude and extent of these changes in r...
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MDPI - Multidisciplinary Digital Publishing Institute
2019
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| Online Access: | Get Fullteks DOAB: description of the publication |
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| LEADER | 04418naaaa2200985uu 4500 | ||
|---|---|---|---|
| 001 | doab_20_500_12854_39900 | ||
| 005 | 20210211 | ||
| 020 | |a books978-3-03921-783-0 | ||
| 020 | |a 9783039217830 | ||
| 020 | |a 9783039217823 | ||
| 024 | 7 | |a 10.3390/books978-3-03921-783-0 |c doi | |
| 041 | 0 | |a English | |
| 042 | |a dc | ||
| 100 | 1 | |a Latifi, Hooman |4 auth | |
| 700 | 1 | |a Valbuena, Ruben |4 auth | |
| 245 | 1 | 0 | |a 3D Remote Sensing Applications in Forest Ecology: Composition, Structure and Function |
| 260 | |b MDPI - Multidisciplinary Digital Publishing Institute |c 2019 | ||
| 300 | |a 1 electronic resource (188 p.) | ||
| 506 | 0 | |a Open Access |2 star |f Unrestricted online access | |
| 520 | |a Dear Colleagues, The composition, structure and function of forest ecosystems are the key features characterizing their ecological properties, and can thus be crucially shaped and changed by various biotic and abiotic factors on multiple spatial scales. The magnitude and extent of these changes in recent decades calls for enhanced mitigation and adaption measures. Remote sensing data and methods are the main complementary sources of up-to-date synoptic and objective information of forest ecology. Due to the inherent 3D nature of forest ecosystems, the analysis of 3D sources of remote sensing data is considered to be most appropriate for recreating the forest's compositional, structural and functional dynamics. In this Special Issue of Forests, we published a set of state-of-the-art scientific works including experimental studies, methodological developments and model validations, all dealing with the general topic of 3D remote sensing-assisted applications in forest ecology. We showed applications in forest ecology from a broad collection of method and sensor combinations, including fusion schemes. All in all, the studies and their focuses are as broad as a forest's ecology or the field of remote sensing and, thus, reflect the very diverse usages and directions toward which future research and practice will be directed. | ||
| 540 | |a Creative Commons |f https://creativecommons.org/licenses/by-nc-nd/4.0/ |2 cc |4 https://creativecommons.org/licenses/by-nc-nd/4.0/ | ||
| 546 | |a English | ||
| 653 | |a normalized difference vegetation index (NDVI) | ||
| 653 | |a SRTMGL1 | ||
| 653 | |a SPOT-6 | ||
| 653 | |a urban ecology | ||
| 653 | |a terrestrial laser scanner | ||
| 653 | |a Lantana camara | ||
| 653 | |a terrestrial laser scanning | ||
| 653 | |a harvester | ||
| 653 | |a product recovery | ||
| 653 | |a imputation | ||
| 653 | |a optimization | ||
| 653 | |a multi-spectral | ||
| 653 | |a function | ||
| 653 | |a ZiYuan-3 stereo images | ||
| 653 | |a spatial noise | ||
| 653 | |a 3D remote sensing | ||
| 653 | |a tree measurement | ||
| 653 | |a diameter at breast height (DBH) | ||
| 653 | |a DSM | ||
| 653 | |a metabolic scale theory | ||
| 653 | |a municipal forestry | ||
| 653 | |a digital photogrammetry | ||
| 653 | |a Norway spruce | ||
| 653 | |a missing observations | ||
| 653 | |a interrater agreement | ||
| 653 | |a measurement error | ||
| 653 | |a stump height | ||
| 653 | |a Fractional cover analysis | ||
| 653 | |a google earth engine | ||
| 653 | |a high-voltage power transmission lines | ||
| 653 | |a habitat fragmentation | ||
| 653 | |a codispersion coefficient | ||
| 653 | |a forest fire | ||
| 653 | |a tree height | ||
| 653 | |a nu SVR | ||
| 653 | |a RapidEye | ||
| 653 | |a uneven-aged mountainous | ||
| 653 | |a random Hough transform | ||
| 653 | |a kriging | ||
| 653 | |a street trees | ||
| 653 | |a ground validation | ||
| 653 | |a Google Street View | ||
| 653 | |a laser | ||
| 653 | |a species identification | ||
| 653 | |a composition | ||
| 653 | |a maximum forest heights | ||
| 653 | |a mountainous areas | ||
| 653 | |a landscape fragmentation | ||
| 653 | |a Landsat 8 | ||
| 653 | |a forest canopy height | ||
| 653 | |a allometric scaling and resource limitation model | ||
| 653 | |a urban forestry | ||
| 653 | |a point cloud | ||
| 653 | |a GSV | ||
| 653 | |a stump diameter | ||
| 653 | |a structure | ||
| 653 | |a 3D | ||
| 653 | |a codispersion map | ||
| 653 | |a forest ecology | ||
| 653 | |a polarimetery | ||
| 653 | |a crowdsourced data | ||
| 856 | 4 | 0 | |a www.oapen.org |u https://mdpi.com/books/pdfview/book/1813 |7 0 |z Get Fullteks |
| 856 | 4 | 0 | |a www.oapen.org |u https://directory.doabooks.org/handle/20.500.12854/39900 |7 0 |z DOAB: description of the publication |