3.2 Prediction of forest cover change
Based on population density, physiography, accessibility and other
factors (Table 3) along with transition probabilities and spatial trend,
this study predicts forest cover scenario for 2023 and 2027. Fig. 5
shows observed versus simulated LULC categories of 2019. The result
clearly demonstrates performance of Markov– CA approach in
simulating LULC. The accuracy of the prediction showed overall accuracy
and kappa of 86.21% and 0.85%, suggesting a good performance of the
model. However, poor simulation was achieved for landcover of mixed
forest and degraded forest categories whilst best agreement was obtained
for agriculture, urban, homestead vegetation categories.
Spatial pattern of land use/covers during 2023 and 2027 is shown in Fig.
6, which indicated that the distribution of degraded forest would be
widespread, if Rohingya camps exist in the peninsula at the expanse of
dominant land covers (e.g., shrubs, mixed forest, plantation forest and
canopy forest). Specifically, shrubs land cover is expected to decline
from 7,306 ha in 2019 to 5,800 and 4,871 ha in 2023 and 2027. Other land
covers such as mixed forest, planted trees and canopy forest would
reduce significantly as well (Table 7). Conversely, a substantial
increase in degraded forest is highly likely during two years (e.g.,
2023 and 2027) though a subtle increase is seen in agriculture and camp
land covers (Table 7).
Forest degradation, as a function of fuelwood collection, illegal
logging and other activities, was determined based on predicted LULC of
2023 and 2027. The analysis revealed that loss of forest cover would
increase dramatically, if present rate of anthropogenic activities
continues in the study area. Since addition of refugee is not expected
due to host country’s repeated denial, it is seen that shrubs, mixed
forest, plantation forest and canopy forest would experience massive
reduction of which loss of shrubs and mixed forest could be substantial
(Table 8).