Abstract
This study investigated the short-term spatial variability of an mangrove patch, located in the Pearl Bay in Guangxi, China. Unmanned aerial vehicle (UAV) imagery covering the period from March 2015 to October 2017 were used and the following models were developed: two annual ultra-high resolution spatial resolution digital orthophoto maps (DOMs), two digital elevation models (DEMs), two digital surface models (DSMs), two canopy height models (CHMs), and a canopy height difference model (d-CHM). Using these models, the spatial dynamics of the extent and canopy height of the patch were analyzed. The resolution of the DOMs was 0.1 m, with an average geometrical error of 0.17 m and a maximum error of 0.44 m. The resolutions of DEMs, DSMs, CHMs, d-CHM were all 1 m. The average elevation errors of CHM in 2015 and 2017 were 0.002 m and -0.001 m, respectively, with maximum absolute errors of 0.034 m and 0.030 m, respectively. The average elevation error of d-CHM was -0.003 m and the maximum absolute error was 0.036 m, and the data quality were rated as good. From 2015 to 2017, the area of the mangrove patch increased from 8.16 ha to 8.79 ha, with an average annual increase of 3.7%. Specifically, the areas of expansion, shrinkage, and maximum seaward expansion were 6356 m2, 19 m2, and 24 m, respectively. The driving factor for the variability was natural processes. Stand canopy height exhibited a particular trend of decrease from northwest to southeast (horizontal; parallel to the seawall) and from the land to the sea (vertically; perpendicular to the seawall). From 2015 to 2017, 88.2% of the patch area showed increased canopy height, with an average increase of 0.78 m and a maximum increase of 3.2 m. In contrast, 11.8% of the patch area showed decreased canopy height with a maximum decrease of 3.1 m. The main reason for the decrease in canopy height was the death of trees caused by serious insect plagues. On the other hand, the reason for the increase in height could be attributed to the natural growth of mangrove trees, but further studies are required to verify the cause. UAV remote sensing has an incomparable advantage over traditional methods in that it provides extremely detailed and highly accurate information for in-depth study of the spatial evolution of mangrove patches, which would significantly contribute towards the protection and management of mangroves.
An analysis of the feeder cattle enterprise on Iowa farms with the use of linear programming techniques