Estimation and mapping of forest stand density, volume, and cover type using the k-nearest neighbors method-Reference-Cited by-同舟云学术

Estimation and mapping of forest stand density, volume, and cover type using the k-nearest neighbors method

Published:2001-09 Issue:3 Volume:77 Page:251-274
ISSN:0034-4257
Container-title:Remote Sensing of Environment
language:en
Short-container-title:Remote Sensing of Environment

Author:

Franco-Lopez Hector,Ek Alan R.,Bauer Marvin E.

Publisher

Elsevier BV

Subject

Computers in Earth Sciences,Geology,Soil Science

Reference48 articles.

1. Albert, D.A. (1995). Regional landscape ecosystems of Michigan, Minnesota, and Wisconsin: a working map and classification. General Technical Report NC-178. St. Paul, MN: North Central Forest Experiment Station, Forest Service, USDA.

2. Anonymous ( 1990). North central region forest inventory and analysis. field instructions: Minnesota (1st ed.). St. Paul, MN: North Central Forest Experiment Station, Forest Service, USDA.

3. Anonymous (1992). Forest service resource inventories: an overview. Washington, DC: Forest Service, Forest Inventory, Economics, and Recreation Research, USDA.

4. Anonymous (1997a). Forest inventory and analysis database retrieval system. Forest Service, USDA. Location: http://www.srsfia.usfs.msstate.edu/scripts/ewdbrs.htm. Date of Access: May 1999.

5. Anonymous (1997b). Imagine. Version 8.3. ERDAS.

Cited by 357 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Updating Forest Stand Inventories: Integration of Photo-Interpreted and Airborne Laser Scanning Forest Attributes Using Generic Region Merging Segmentation and kNN Imputation;Canadian Journal of Remote Sensing;2024-09-12

2. Spatial Resolution Impacts on Land Cover Mapping Accuracy;Journal of the Indian Society of Remote Sensing;2024-08-06

3. Machine learning approaches to predict the strength of graphene nanoplatelets concrete: Optimization and hyper tuning with graphical user interface;Materials Today Communications;2024-08

4. Identification of novel NLRP3 inhibitors as therapeutic options for epilepsy by machine learning-based virtual screening, molecular docking and biomolecular simulation studies;Heliyon;2024-08

5. Machine learning feature importance selection for predicting aboveground biomass in African savannah with landsat 8 and ALOS PALSAR data;Machine Learning with Applications;2024-06