Hladik et al., 2013 - Google Patents
Salt marsh elevation and habitat mapping using hyperspectral and LIDAR dataHladik et al., 2013
- Document ID
- 1942145409658227477
- Author
- Hladik C
- Schalles J
- Alber M
- Publication year
- Publication venue
- Remote Sensing of Environment
External Links
Snippet
Accurate mapping of both elevation and plant distributions in salt marshes is important for management and conservation goals. Although light detection and ranging (LIDAR) is effective at measuring surface elevations, laser penetration is limited in dense salt marsh …
- 239000011780 sodium chloride 0 title abstract description 101
Classifications
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06K—RECOGNITION OF DATA; PRESENTATION OF DATA; RECORD CARRIERS; HANDLING RECORD CARRIERS
- G06K9/00—Methods or arrangements for reading or recognising printed or written characters or for recognising patterns, e.g. fingerprints
- G06K9/00624—Recognising scenes, i.e. recognition of a whole field of perception; recognising scene-specific objects
- G06K9/0063—Recognising patterns in remote scenes, e.g. aerial images, vegetation versus urban areas
- G06K9/00657—Recognising patterns in remote scenes, e.g. aerial images, vegetation versus urban areas of vegetation
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T17/00—Three dimensional [3D] modelling, e.g. data description of 3D objects
- G06T17/05—Geographic models
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06K—RECOGNITION OF DATA; PRESENTATION OF DATA; RECORD CARRIERS; HANDLING RECORD CARRIERS
- G06K9/00—Methods or arrangements for reading or recognising printed or written characters or for recognising patterns, e.g. fingerprints
- G06K9/36—Image preprocessing, i.e. processing the image information without deciding about the identity of the image
- G06K9/46—Extraction of features or characteristics of the image
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T2207/00—Indexing scheme for image analysis or image enhancement
- G06T2207/10—Image acquisition modality
- G06T2207/10032—Satellite or aerial image; Remote sensing
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06K—RECOGNITION OF DATA; PRESENTATION OF DATA; RECORD CARRIERS; HANDLING RECORD CARRIERS
- G06K9/00—Methods or arrangements for reading or recognising printed or written characters or for recognising patterns, e.g. fingerprints
- G06K9/20—Image acquisition
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T11/00—2D [Two Dimensional] image generation
- G06T11/20—Drawing from basic elements, e.g. lines or circles
- G06T11/206—Drawing of charts or graphs
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06Q—DATA PROCESSING SYSTEMS OR METHODS, SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL, SUPERVISORY OR FORECASTING PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL, SUPERVISORY OR FORECASTING PURPOSES, NOT OTHERWISE PROVIDED FOR
- G06Q40/00—Finance; Insurance; Tax strategies; Processing of corporate or income taxes
- G06Q40/06—Investment, e.g. financial instruments, portfolio management or fund management
Similar Documents
Publication | Publication Date | Title |
---|---|---|
Hladik et al. | Salt marsh elevation and habitat mapping using hyperspectral and LIDAR data | |
Mao et al. | National wetland mapping in China: A new product resulting from object-based and hierarchical classification of Landsat 8 OLI images | |
Hladik et al. | Accuracy assessment and correction of a LIDAR-derived salt marsh digital elevation model | |
Byrd et al. | Evaluation of sensor types and environmental controls on mapping biomass of coastal marsh emergent vegetation | |
Walker et al. | Evaluation of Landsat and MODIS data fusion products for analysis of dryland forest phenology | |
Roberts et al. | Relationships between dominant plant species, fractional cover and land surface temperature in a Mediterranean ecosystem | |
Chimner et al. | Mapping mountain peatlands and wet meadows using multi-date, multi-sensor remote sensing in the Cordillera Blanca, Peru | |
Saha et al. | Land cover classification using IRS LISS III image and DEM in a rugged terrain: a case study in Himalayas | |
Colditz et al. | Land cover classification with coarse spatial resolution data to derive continuous and discrete maps for complex regions | |
Alonzo et al. | Mapping tall shrub biomass in Alaska at landscape scale using structure-from-motion photogrammetry and lidar | |
Hüttich et al. | Assessing effects of temporal compositing and varying observation periods for large-area land-cover mapping in semi-arid ecosystems: Implications for global monitoring | |
Dheeravath et al. | Irrigated areas of India derived using MODIS 500 m time series for the years 2001–2003 | |
Yaney-Keller et al. | Using Unmanned Aerial Systems (UAS) to assay mangrove estuaries on the Pacific coast of Costa Rica | |
Morgan et al. | Spatiotemporal analysis of vegetation cover change in a large ephemeral river: Multi-sensor fusion of unmanned aerial vehicle (uav) and landsat imagery | |
Mbaabu et al. | Quantification of carbon stock to understand two different forest management regimes in Kayar Khola watershed, Chitwan, Nepal | |
Zhang et al. | Comparison of TanDEM-X DEM with LiDAR data for accuracy assessment in a coastal urban area | |
Puzachenko et al. | Assessing the thermodynamic variables of landscapes in the southwest part of East European plain in Russia using the MODIS multispectral band measurements | |
Zhang et al. | Applying time series Landsat data for vegetation change analysis in the Florida Everglades Water Conservation Area 2A during 1996–2016 | |
Zeng et al. | Assessment of the patterns of urban land covers and impervious surface areas: A case study of Shenzhen, China | |
Collier et al. | Mapping biological soil crusts in a Hawaiian dryland | |
Creutzfeldt | Remote sensing based characterisation of land cover and terrain properties for hydrological modelling in the semi-arid Northeast of Brazil | |
Sensing | Wetland mapping methods and techniques using multisensor, multiresolution remote sensing: successes and challenges | |
Waser | Airborne remote sensing data for semi-automated extraction of tree area and classification of tree species | |
CN112052720B (en) | High-space-time normalization vegetation index NDVI fusion model based on histogram clustering | |
Guo et al. | Research on regional soil moisture dynamics based on hyperspectral remote sensing technology |