Using Naip Imagery To Estimate Tree Canopy Cover

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Using Naip Imagery To Estimate Tree Canopy Cover

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Author : Abigail Schaaf
language : en
Publisher:
Release Date : 2010

Using Naip Imagery To Estimate Tree Canopy Cover written by Abigail Schaaf and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2010 with categories.

This paper highlights the likelihood of overestimating canopy cover using any airborne imagerywith particular focus on National Agriculture Imagery Program (NAIP) imagery. This study compared canopy-cover estimates from NAIP imagery and resource photography acquired during the same year. Four sites were selected based on a visual evaluation of apparent canopy-cover differences between the two types of imagery and used to estimate tree canopy cover. The estimates of canopy cover samples from NAIP imagery were about 45 percent higher than those collected from resource photography. Because NAIP is the only high-resolution digital imagery available over the contiguous U.S. (and is streamed via Image Server to all Forest Service personnel), it is an important resource for forest mapping, planning, and monitoring. However, it does have limitations, specifically estimating canopy cover. The results from this investigation need to be considered before deciding to use NAIP imagery to determine tree canopy cover."

Image Based Estimation Of Urban Tree Canopy Cover In Support Of The Urban Forest Effects Ufore Model

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Author :
language : en
Publisher:
Release Date : 2014

Image Based Estimation Of Urban Tree Canopy Cover In Support Of The Urban Forest Effects Ufore Model written by and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2014 with categories.

Tools such as the Urban Forest Effects (UFORE) model exist to convert measured quantities of the physical state of urban forests into monetary sums that represent the ecosystem services that the forests provide. However, field data required to run the model are infrequently collected and very costly to acquire. Remotely sensed data may provide a cost-effective way to collect canopy cover data, one of the data requirements for the UFORE model, to augment and extend the life of the field data. The purpose of this study is to create a simple and repeatable workflow that accurately characterizes forest canopy cover using high resolution remotely sensed data. Student volunteers were trained in image interpretation techniques and then estimated canopy cover for a pilot study area in Tampa, FL. A total of 531 1/10-acre plots (each with 29 systematically distributed points) were interpreted as either 'tree' or 'non-tree' using 2006 IKONOS imagery pan-sharpened to 1 meter and 2010 1-meter 4-band color infrared NAIP imagery. Canopy cover estimates were then compared to field data collected in 2006 and 2011, respectively, and used to train a supervised classification to produce a wall-to-wall map product. Classification resulted in poor overall accuracy for 2006 and 2010 maps, and wall-to-wall products were deemed not acceptable and thus discarded in favor of the image-based estimation. However, comparisons of interpreted points (32.87 percent plus or minus 3.01 percent and 31.35 percent plus or minus 2.91 percent for 2006 and 2010, respectively) and field data (31.30 percent plus or minus 2.79 percent and 33.26 plus or minus 2.87 percent for 2006 and 2011, respectively) indicate strong positive relationships and demonstrate that while considerable resources must be invested to train new interpreters, remotely sensed data can provide an adequate surrogate for field-collected canopy cover data in gap collection years.

Estimating Piyon And Juniper Cover Across Utah Using Naip Imagery

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Author : Darrell B. Roundy
language : en
Publisher:
Release Date : 2015

Estimating Piyon And Juniper Cover Across Utah Using Naip Imagery written by Darrell B. Roundy and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2015 with Electronic Dissertations categories.

Forest Structure Estimates From Naip Point Cloud Data

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Author :
language : en
Publisher:
Release Date : 2017

Forest Structure Estimates From Naip Point Cloud Data written by and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2017 with categories.

The U.S. Department of Agriculture, Forest Service uses mid-level vegetation maps for forest plan revisions and other forest planning tasks. The maps are composed of image segments that are attributed using data-mining tools to include dominant cover-type, canopy cover class, and tree size class. Although these map layers provide useful structure information, they lack canopy height information. In addition, the canopy cover and tree size layers are modeled from field collected or image interpreted training data, which can be resource intensive. One method for obtaining forest structure information is by using lidar data. However, lidar acquisitions can be cost prohibitive for forest-wide mapping and monitoring efforts. Stereo aerial imagery, which is less expensive and acquired more frequently than lidar, is another method for obtaining forest structure information. In 2015, multiple federal and state agencies purchased a 3D point cloud for the entire state of Wyoming as part of the National Agriculture Imagery Program (NAIP) contract. The goal of this study was to evaluate the suitability of using the NAIP point cloud to update and improve FS mid-level vegetation maps. To accomplish this, we created canopy cover and height products from the NAIP and used an independent lidar point cloud as a reference dataset for a portion of the Bridger-Teton National Forest. Mean values from each product were summarized and compared at the vegetation map segment level. Root mean square error (RMSE) values ranged from 4.28 to 18.43 percent for canopy cover and 2.09 to 8.72 m for canopy height. In addition, allometric equations for tree size were derived by using a combination of canopy height and the existing cover-type information. A workflow was developed for updating the existing mid-level vegetation maps with the canopy cover, height, and tree size information. The NAIP point cloud products were found to provide similar information as the lidar products under certain conditions, but contained many more errors and lacked the detail of the lidar data. In addition, the NAIP point cloud relied heavily on the lidar digital terrain model (DTM) to produce the canopy cover and height products. Future studies could explore methods for improving the NAIP point clouds and derived products.

Estimating Forest Canopy Attributes Via Airborne High Resolution Multispectral Imagery In Midwest Forest Types

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Author : Demetrios Gatziolis
language : en
Publisher:
Release Date : 2003

Estimating Forest Canopy Attributes Via Airborne High Resolution Multispectral Imagery In Midwest Forest Types written by Demetrios Gatziolis and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2003 with Forest canopy ecology categories.

Comparison Of Urban Tree Canopy Classification With High Resolution Satellite Imagery And Three Dimensional Data Derived From Lidar And Stereoscopic Sensors

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Author :
language : en
Publisher:
Release Date : 2008

Comparison Of Urban Tree Canopy Classification With High Resolution Satellite Imagery And Three Dimensional Data Derived From Lidar And Stereoscopic Sensors written by and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2008 with Remote sensing categories.

Despite growing recognition as a significant natural resource, methods for accurately estimating urban tree canopy cover extent and change over time are not well-established. This study evaluates new methods and data sources for mapping urban tree canopy cover, assessing the potential for increased accuracy by integrating high-resolution satellite imagery and 3D imagery derived from LIDAR and stereoscopic sensors. The results of urban tree canopy classifications derived from imagery, 3D data, and vegetation index data are compared across multiple urban land use types in the City of Indianapolis, Indiana. Results indicate that incorporation of 3D data and vegetation index data with high resolution satellite imagery does not significantly improve overall classification accuracy. Overall classification accuracies range from 88.34% to 89.66%, with resulting overall Kappa statistics ranging from 75.08% to 78.03%, respectively. Statistically significant differences in accuracy occurred only when high resolution satellite imagery was not included in the classification treatment and only the vegetation index data or 3D data were evaluated. Overall classification accuracy for these treatment methods were 78.33% for both treatments, with resulting overall Kappa statistics of 51.36% and 52.59%.

Los Angeles 1 Million Tree Canopy Cover Assessment

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Author : United States Department of Agriculture
language : en
Publisher: CreateSpace
Release Date : 2015-06-26

Los Angeles 1 Million Tree Canopy Cover Assessment written by United States Department of Agriculture and has been published by CreateSpace this book supported file pdf, txt, epub, kindle and other format this book has been release on 2015-06-26 with categories.

The Million Trees LA initiative intends to chart a course for sustainable growth through planting and stewardship of trees. The purpose of this study was to measure Los Angeles's existing tree canopy cover (TCC), determine if space exists for 1 million additional trees, and estimate future benefits from the planting. Highresolution QuickBird remote sensing data, aerial photographs, and geographic information systems were used to classify land cover types, measure TCC, and identify potential tree planting sites.

Urban Ecosystem Services

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Author : Alessio Russo
language : en
Publisher: MDPI
Release Date : 2021-05-07

Urban Ecosystem Services written by Alessio Russo and has been published by MDPI this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-05-07 with Science categories.

The school of thought surrounding the urban ecosystem has increasingly become in vogue among researchers worldwide. Since half of the world’s population lives in cities, urban ecosystem services have become essential to human health and wellbeing. Rapid urban growth has forced sustainable urban developers to rethink important steps by updating and, to some degree, recreating the human–ecosystem service linkage. Assessing, as well as estimating the losses of ecosystem services can denote the essential effects of urbanization and increasingly indicate where cities fall short. This book contains 13 thoroughly refereed contributions published within the Special Issue “Urban Ecosystem Services”. The book addresses topics such as nature-based solutions, green space planning, green infrastructure, rain gardens, climate change, and more. The contributions highlight new findings for landscape architects, urban planners, and policymakers. Important future cities research is considered by looking at the system connectivity between the social and ecological sphere—via varying forms of urban planning, management, and governance. The book is supported by methods and models that utilize an urban sustainability and ecosystem service-centric focus by adding knowledge-base and real-world solutions into the urbanization phenomenon.

Forestry Applications Of Unmanned Aerial Vehicles Uavs 2019

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Author : Alessandro Matese
language : en
Publisher: MDPI
Release Date : 2020-11-23

Forestry Applications Of Unmanned Aerial Vehicles Uavs 2019 written by Alessandro Matese and has been published by MDPI this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-11-23 with Science categories.

Unmanned aerial vehicles (UAVs) are new platforms that have been increasingly used in the last few years for forestry applications that benefit from the added value of flexibility, low cost, reliability, autonomy, and capability of timely provision of high-resolution data. The main adopted image-based technologies are RGB, multispectral, and thermal infrared. LiDAR sensors are becoming commonly used to improve the estimation of relevant plant traits. In comparison with other permanent ecosystems, forests are particularly affected by climatic changes due to the longevity of the trees, and the primary objective is the conservation and protection of forests. Nevertheless, forestry and agriculture involve the cultivation of renewable raw materials, with the difference that forestry is less tied to economic aspects and this is reflected by the delay in using new monitoring technologies. The main forestry applications are aimed toward inventory of resources, map diseases, species classification, fire monitoring, and spatial gap estimation. This Special Issue focuses on new technologies (UAV and sensors) and innovative data elaboration methodologies (object recognition and machine vision) for applications in forestry.

Modeling Percent Shrub Canopy Cover And Bare Ground

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Author :
language : en
Publisher:
Release Date : 2014

Modeling Percent Shrub Canopy Cover And Bare Ground written by and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2014 with Deschutes National Forest categories.

The development of geospatial data reflecting current amounts of tree, shrub, herbaceous, bare-ground and water cover is key to improving the USDA Forest Service's capacity to manage land. We assessed the use of image-sampled tree, shrub, herbaceous, bare ground and water estimates from National Agriculture Imagery Program (NAIP) data for constructing empirical models to estimate and map vegetation composition at unmeasured locations. While particular focus was on percent shrub cover and bare ground, predictive models were constructed for all five cover types in order to look at the potential benefit of a more integrated approach for modeling these different cover types. Two different modeling methods were explored: 1) a univariate approach based on random forests, and 2) a multivariate approach based on bootstrap nearest neighbors. Under both modeling approaches the rank order of model accuracy, according to pseudo-R2, was water, tree, herbaceous, other cover, shrub, and bare ground. Generally, the pseudo-R2 values for the two approaches were similar for each cover type. Unfortunately the shrub and bare ground cover types proved to be the most difficult to model (R2 was 0.37 for shrub and 0.27 for bare ground). Alone, these modeling results for shrub and bare ground may not be adequate for spatially explicit management purposes, but when created in conjunction with other cover types (which have higher R2 values) they may have more merit. This is particularly true for analysis applications that evaluate multiple land cover types concurrently and require area estimates and maps that are analytically consistent and logically sum to realistic totals.