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RSS FeedsRemote Sensing, Vol. 11, Pages 2195: Investigating the Impact of Land Parcelization on Forest Composition and Structure in Southeastern Ohio Using Multi-Source Remotely Sensed Data (Remote Sensing)

 
 

20 september 2019 17:00:50

 
Remote Sensing, Vol. 11, Pages 2195: Investigating the Impact of Land Parcelization on Forest Composition and Structure in Southeastern Ohio Using Multi-Source Remotely Sensed Data (Remote Sensing)
 


Forestland parcelization (i.e., a process by which large parcels of forestland ownership are divided into many small parcels) presents an increasing challenge to sustainable forest development in the United States. In Southeastern Ohio, forests also experienced intensive forestland parcelization, where the majority of forest owners own parcels smaller than 10 acres currently. To better understand the impact of forestland parcelization on forest development, this study employed multi-source remotely sensed data and land ownership data in Hocking County, Ohio to examine the relationship between forestland parcel size and forest attributes, including forest composition and structure. Our results show that private forestland parcels are generally smaller than public forestland (the average parcel sizes are 21.5 vs. 275.0 acres). Compared with private lands, public lands have higher values in all forest attributes, including forest coverage, abundance of oak-dominant stands, canopy height and aboveground biomass. A further investigation focusing on private forestland reveals that smaller parcels tend to have smaller forest coverage, less greenness, lower height and aboveground biomass, indicating that forests in smaller parcels may experience more human disturbances than larger parcels. The results also show that logarithmic models can well quantify the non-linear relationship between forest attributes and parcel size in the study area. Our study suggests that forestland parcelization indeed has negative effects on forest development, so it is very important to take appropriate measures to protect forests in small ownership parcels.


 
248 viewsCategory: Geology, Physics
 
Remote Sensing, Vol. 11, Pages 2196: Integration of Automatic Identification System (AIS) Data and Single-Channel Synthetic Aperture Radar (SAR) Images by SAR-Based Ship Velocity Estimation for Maritime Situational Awareness (Remote Sensing)
Remote Sensing, Vol. 11, Pages 2193: Conditional Generative Adversarial Networks (cGANs) for Near Real-Time Precipitation Estimation from Multispectral GOES-16 Satellite Imageries--PERSIANN-cGAN (Remote Sensing)
 
 
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