scholarly journals Grain and Extent Considerations Are Integral for Monitoring Landscape-Scale Desired Conditions in Fire-Adapted Forests

Forests ◽  
2019 ◽  
Vol 10 (6) ◽  
pp. 465
Author(s):  
Tzeidle N. Wasserman ◽  
Andrew J. Sánchez Meador ◽  
Amy E. M. Waltz
Keyword(s):  
Landscape Metrics ◽  
Spatial Data ◽  
Forest Canopy ◽  
Canopy Cover ◽  
Remotely Sensed ◽  
Landscape Scale ◽  
Landsat 8 ◽  
Landscape Characteristics ◽  
Data Product ◽  
Data Products

Remotely-sensed data are commonly used to evaluate forest metrics, such as canopy cover, to assess change detection, and to inform land management planning. Often, canopy cover is measured only at the scale of the spatial data product used in the analysis, and there is a mismatch between the management question and the scale of the data. We compared four readily available remotely sensed landscape data products— Light detection and ranging (LiDAR), Landsat-8, Sentinel-2, and National Agriculture Imagery Program (NAIP) imagery —at different spatial grains and multiple extents to assess their consistency and efficacy for quantifying key landscape characteristics of forest canopy patches and sensitivity to change. We examined landscape-scale patterns of forest canopy cover across three landscapes in northern Arizona and assessed their performance using six landscape metrics. Changes in grain and extent affect canopy cover patch metrics and the inferences that can be made from each data product. Overall data products performed differently across landscape metrics. When performing analyses and choosing data layers, it is essential to match the scale of the data product to the management question and understand the limitations inherent in using canopy cover as a stand-alone metric.

scholarly journals Shade-tree rehabilitation in vanilla agroforests is yield neutral and may translate into landscape-scale canopy cover gains

2020 ◽  
Author(s):  
Dominic A. Martin ◽  
Annemarie Wurz ◽  
Kristina Osen ◽  
Ingo Grass ◽  
Dirk Hölscher ◽  
...  
Keyword(s):  
Forest Canopy ◽  
Agricultural Landscape ◽  
Canopy Cover ◽  
Landscape Scale ◽  
Tree Cover ◽  
Ecosystem Functions ◽  
Forest Fragments ◽  
Forest Protection ◽  
Shade Tree ◽  
Open Land

Agroforestry can contribute to an increase in tree cover in historically forested tropical landscapes with associated gains in biodiversity and ecosystem functioning, but only if established on open land instead of underneath a forest canopy. However, declines in yields with increasing shade are common across agroforestry crops, driving shade-tree removal in forest-derived agroforests and hindering tree regrowth in open-land-derived agroforests. To understand trajectories of change in tree cover in forest- and open-land-derived agroforests and the impacts of tree cover on vanilla yields, we studied 209 vanilla agroforests along an 88-year chronosequence in Madagascar. Additionally, we used remotely-sensed canopy cover data to investigate tree cover change in the agricultural landscape. We found yields to vary widely but independently of canopy cover and land-use history (forest- vs. open-land-derived), averaging at 154.6 kg ha-1 yr-1 (SD = 186.9). Furthermore, we found that forest- and open-land-derived vanilla agroforests gained canopy cover over time, but that only open-land-derived agroforests gained canopy height. Canopy cover increased also at the landscape scale: areas in the agricultural landscape with medium initial canopy cover gained 6.4% canopy cover over 10 years, but canopy cover decreased in areas with high initial canopy cover. These opposing trends suggest tree cover rehabilitation across areas covered by vanilla agroforests, whereas remnant forest fragments in the agricultural landscape were transformed or degraded. Our results indicate that yield-neutral tree rehabilitation through open-land-derived agroforestry could, if coupled with effective forest protection, provide mutually beneficial outcomes for ecosystem functions and agricultural production in a smallholder-dominated agricultural landscape.

Comparison of Sentinel-2 and Landsat 8 in the estimation of boreal forest canopy cover and leaf area index

2017 ◽  
Vol 195 ◽  
pp. 259-274 ◽  
Author(s):  
Lauri Korhonen ◽  
Hadi ◽  
Petteri Packalen ◽  
Miina Rautiainen
Keyword(s):  
Boreal Forest ◽  
Leaf Area Index ◽  
Leaf Area ◽  
Forest Canopy ◽  
Canopy Cover ◽  
Landsat 8 ◽  
Area Index ◽  
Sentinel 2

scholarly journals Shade-Tree Rehabilitation in Vanilla Agroforests is Yield Neutral and May Translate into Landscape-Scale Canopy Cover Gains

Ecosystems ◽  
2020 ◽  
Author(s):  
Dominic Andreas Martin ◽  
Annemarie Wurz ◽  
Kristina Osen ◽  
Ingo Grass ◽  
Dirk Hölscher ◽  
...  
Keyword(s):  
Forest Canopy ◽  
Agricultural Landscape ◽  
Canopy Cover ◽  
Landscape Scale ◽  
Tree Cover ◽  
Ecosystem Functions ◽  
Forest Fragments ◽  
Forest Protection ◽  
Shade Tree ◽  
Open Land

AbstractAgroforestry can contribute to an increase in tree cover in historically forested tropical landscapes with associated gains in biodiversity and ecosystem functioning, but only if established on open land instead of underneath a forest canopy. However, declines in yields with increasing shade are common across agroforestry crops, driving shade-tree removal in forest-derived agroforests and hindering tree regrowth in open-land-derived agroforests. To understand trajectories of change in tree cover in forest- and open-land-derived agroforests, and the impacts of tree cover on vanilla yields, we studied 209 vanilla agroforests along an 88-year chronosequence in Madagascar. Additionally, we used remotely sensed canopy cover data to investigate tree cover change in the agricultural landscape. We found yields to vary widely but independently of canopy cover and land-use history (forest- vs. open-land-derived), averaging at 154.6 kg ha−1 year−1 (SD = 186.9). Furthermore, we found that forest- and open-land-derived vanilla agroforests gained canopy cover over time, but that only open-land-derived agroforests gained canopy height. Canopy cover increased also at the landscape scale: areas in the agricultural landscape with medium initial canopy cover gained 6.4% canopy cover over 10 years, but canopy cover decreased in areas with high initial canopy cover. These opposing trends suggest tree cover rehabilitation across areas covered by vanilla agroforests, whereas remnant forest fragments in the agricultural landscape were transformed or degraded. Our results indicate that yield-neutral tree rehabilitation through open-land-derived agroforestry could, if coupled with effective forest protection, provide benefits for both ecosystem functions and agricultural production in a smallholder-dominated agricultural landscape.

scholarly journals Estimating Forest Canopy Cover by Multiscale Remote Sensing in Northeast Jiangxi, China

Land ◽  
2021 ◽  
Vol 10 (4) ◽  
pp. 433
Author(s):  
Xiaolan Huang ◽  
Weicheng Wu ◽  
Tingting Shen ◽  
Lifeng Xie ◽  
Yaozu Qin ◽  
...  
Keyword(s):  
Remote Sensing ◽  
Large Scale ◽  
Forest Canopy ◽  
Canopy Cover ◽  
Google Earth ◽  
Tree Canopy ◽  
Landsat Data ◽  
High Resolution Data ◽  
Modis Ndvi ◽  
Tree Canopy Cover

This research was focused on estimation of tree canopy cover (CC) by multiscale remote sensing in south China. The key aim is to establish the relationship between CC and woody NDVI (NDVIW) or to build a CC-NDVIW model taking northeast Jiangxi as an example. Based on field CC measurements, this research used Google Earth as a complementary source to measure CC. In total, 63 sample plots of CC were created, among which 45 were applied for modeling and the remaining 18 were employed for verification. In order to ascertain the ratio R of NDVIW to the satellite observed NDVI, a 20-year time-series MODIS NDVI dataset was utilized for decomposition to obtain the NDVIW component, and then the ratio R was calculated with the equation R = (NDVIW/NDVI) *100%, respectively, for forest (CC >60%), medium woodland (CC = 25–60%) and sparse woodland (CC 1–25%). Landsat TM and OLI images that had been orthorectified by the provider USGS were atmospherically corrected using the COST model and used to derive NDVIL. R was multiplied for the NDVIL image to extract the woody NDVI (NDVIWL) from Landsat data for each of these plots. The 45 plots of CC data were linearly fitted to the NDVIWL, and a model with CC = 103.843 NDVIW + 6.157 (R2 = 0.881) was obtained. This equation was applied to predict CC at the 18 verification plots and a good agreement was found (R2 = 0.897). This validated CC-NDVIW model was further applied to the woody NDVI of forest, medium woodland and sparse woodland derived from Landsat data for regional CC estimation. An independent group of 24 measured plots was utilized for validation of the results, and an accuracy of 83.0% was obtained. Thence, the developed model has high predictivity and is suitable for large-scale estimation of CC using high-resolution data.

Forest canopy cover analysis using UAS lidar

2017 ◽  
Author(s):  
Qingwang Liu ◽  
Shiming Li ◽  
Kailong Hu ◽  
Yong Pang ◽  
Zengyuan Li
Keyword(s):  
Forest Canopy ◽  
Canopy Cover

scholarly journals Landscape-scale quantification of fire-induced change in canopy cover following mountain pine beetle outbreak and timber harvest

2017 ◽  
Vol 391 ◽  
pp. 164-175 ◽  
Author(s):  
T. Ryan McCarley ◽  
Crystal A. Kolden ◽  
Nicole M. Vaillant ◽  
Andrew T. Hudak ◽  
Alistair M.S. Smith ◽  
...  
Keyword(s):  
Mountain Pine Beetle ◽  
Canopy Cover ◽  
Timber Harvest ◽  
Landscape Scale ◽  
Mountain Pine ◽  
Pine Beetle

Mapping wildlife: integrating stakeholder knowledge with modelled patterns of deer abundance by using participatory GIS

2009 ◽  
Vol 36 (7) ◽  
pp. 553 ◽  
Author(s):  
Z. Austin ◽  
S. Cinderby ◽  
J. C. R. Smart ◽  
D. Raffaelli ◽  
P. C. L. White
Keyword(s):  
Community Involvement ◽  
Spatial Data ◽  
Spatial Scales ◽  
Stakeholder Participation ◽  
Landscape Scale ◽  
Scientific Data ◽  
Future Research ◽  
Economic Damage ◽  
Participatory Gis ◽  
Wild Deer

Context. Some species that are perceived by certain stakeholders as a valuable resource can also cause ecological or economic damage, leading to contrasting management objectives and subsequent conflict between stakeholder groups. There is increasing recognition that the integration of stakeholder knowledge with formal scientific data can enhance the information available for use in management. This is especially true where scientific understanding is incomplete, as is frequently the case for wide-ranging species, which can be difficult to monitor directly at the landscape scale. Aims. The aim of the research was to incorporate stakeholder knowledge with data derived from formal quantitative models to modify predictions of wildlife distribution and abundance, using wild deer in the UK as an example. Methods. We use selected predictor variables from a deer–vehicle collision model to estimate deer densities at the 10-km square level throughout the East of England. With these predictions as a baseline, we illustrate the use of participatory GIS as a methodological framework for enabling stakeholder participation in the refinement of landscape-scale deer abundance maps. Key results. Stakeholder participation resulted in modifications to modelled abundance patterns for all wild deer species present in the East of England, although the modifications were minor and there was a high degree of consistency among stakeholders in the adjustments made. For muntjac, roe and fallow deer, the majority of stakeholder changes represented an increase in density, suggesting that populations of these species are increasing in the region. Conclusions. Our results show that participatory GIS is a useful technique for enabling stakeholders to contribute to incomplete scientific knowledge, especially where up-to-date species distribution and abundance data are needed to inform wildlife research and management. Implications. The results of the present study will serve as a valuable information base for future research on deer management in the region. The flexibility of the approach makes it applicable to a range of species at different spatial scales and other wildlife conflict issues. These may include the management of invasive species or the conservation of threatened species, where accurate spatial data and enhanced community involvement are necessary in order to facilitate effective management.

The accuracy of large-area forest canopy cover estimation using Landsat in boreal region

2016 ◽  
Vol 53 ◽  
pp. 118-127 ◽  
Author(s):  
Hadi ◽  
Lauri Korhonen ◽  
Aarne Hovi ◽  
Petri Rönnholm ◽  
Miina Rautiainen
Keyword(s):  
Forest Canopy ◽  
Canopy Cover ◽  
Large Area ◽  
Boreal Region

scholarly journals Scientific Knowledge Mobilization: Co-evolution of Data Products and Designated Communities

2016 ◽  
Vol 10 (2) ◽  
pp. 110-135 ◽  
Author(s):  
Karen S. Baker ◽  
Ruth E. Duerr ◽  
Mark A. Parsons
Keyword(s):  
Product Development ◽  
Scientific Knowledge ◽  
Greenland Ice Sheet ◽  
Remote Sensing Data ◽  
Knowledge Bases ◽  
Digital Data ◽  
Knowledge Mobilization ◽  
Data Product ◽  
Community Interest ◽  
Data Products

Digital data are accumulating rapidly, yet issues relating to data production remain unexamined. Data sharing efforts in particular are nascent, disunited and incomplete. We investigate the development of data products tailored for diverse communities with differing knowledge bases. We explore not the technical aspects of how, why, or where data are made available, but rather the socio-scientific aspects influencing what data products are created and made available for use. These products differ from compact data summaries often published in journals. We report on development by a national data center of two data collections describing the changing polar environment. One collection characterizes sea ice products derived from satellite remote sensing data and development unfolds over three decades. The second collection characterizes the Greenland Ice Sheet melt where development of an initial collection of data products over a period of several months was informed by insights gained from earlier experience. In documenting the generation of these two collections, a data product development cycle supported by a data product team is identified as key to mobilizing scientific knowledge. The collections reveal a co-evolution of data products and designated communities where community interest may be triggered by events such as environmental disturbance and new modes of communication. These examples of data product development in practice illustrate knowledge mobilization in the earth sciences; the collections create a bridge between data producers and a growing number of audiences interested in making evidence-based decisions.  

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