Changes in the area of inland lakes in arid regions of central Asia during the past 30 years

Inland lakes are major surface water resource in arid regions of Central Asia. The area changes in these lakes have been proved to be the results of regional climate changes and recent human activities. This study aimed at investigating the area variations of the nine major lakes in Central Asia over the last 30 years. Firstly, multi-temporal Landsat imagery in 1975, 1990, 1999, and 2007 were used to delineate lake extents automatically based on Normalized Difference Water Index (NDWI) threshold segmentation, then lake area variations were detailed in three decades and the mechanism of these changes was analyzed with meteorological data and hydrological data. The results indicated that the total surface areas of these nine lakes had decreased from 91,402.06 km² to 46,049.23 km² during 1975?C2007, accounting for 49.62% of their original area of 1975. Tail-end lakes in flat areas had shrunk dramatically as they were induced by both climate changes and human impacts, while alpine lakes remained relatively stable due to the small precipitation variations. With different water usage of river outlets, the variations of open lakes were more flexible than those of other two types. According to comprehensive analyses, different types of inland lakes presented different trends of area changes under the background of global warming effects in Central Asia, which showed that the increased human activities had broken the balance of water cycles in this region.     

Monitoring urban growth and detecting land-cover changes on the Istanbul metropolitan area

Istanbul is the most populated city of Turkey with a population of around 10.58 M (2000) living on around 5,750 km². In 1980, the population was only 4.7 M and then it has been more than doubled in only two decades. The population has been increasing as a result of mass immigration. An urbanization process continues and it causes serious increases in urban areas while decreasing the amount of green areas. This rapid, uncontrolled, and illegal urbanization accompanied by insufficient infrastructure has caused degradation of forest and barren lands in the metropolitan area, especially through the last two decades. The watershed basins inside the metropolitan area and the transportation network have accelerated the land-cover changes, which have negative impacts on water quality of the basins. Monitoring urban growth and land cover change will enable better management of this complex urban area by the Greater Istanbul Metropolitan Municipality (GIMM). A temporal assessment of land-cover changes of Istanbul has been documented in this study. The study mainly focuses on the acquisition and analysis of Landsat TM and Landsat GeoCover LC satellite images reflecting the significant land-cover changes between the years of 1990 and 2005. Raster data were converted to vector data and used in Geographic Information Systems (GIS). A database was created for Istanbul metropolitan area to plan, manage, and utilize statistical attribute data covering population, water, forest, industry, and topographic position. Consequently an overlay analysis was carried out and land use/cover changes through years have been detected for the case study area. The capability of Landsat images in determining the alterations in the macro form of the city are also discussed.     

Using Landsat image time series to study a small water body in Northern Spain

Ramsar Convention and EU Water Framework Directive are two international agreements focused on the conservation and achievement of good ecological and chemical status of wetlands. Wetlands are important ecosystems holding many plant and animal communities. Their environmental status can be characterised by the quality of their water bodies. Water quality can be assessed from biophysical parameters (such as Chlorophyll-a concentration ([Chla]), water surface temperature and transparency) in the deeper or lacustrine zone, or from bioindicators (as submerged aquatic vegetation) in the shallow or palustrine zone. This paper proves the use of Landsat time series to measure the evolution of water quality parameters and the environmental dynamics of a small water body (6.57 ha) in a Ramsar wetland (Arreo Lake in the North of Spain). Our results show that Landsat TM images can be used to describe periodic behaviours such as the water surface temperature or the phenologic state of the submerged vegetation (through normalized difference vegetation index, NDVI) and thus detect anomalous events. We also show how [Chla] and transparency can be measured in the lacustrine zone using Landsat TM images and an algorithm adjusted for mesotrophic Spanish lakes, and the resulting values vary in time in accordance with field measurements (although these were not synchronous with the images). The availability of this algorithm also highlights anomalies in the field data series that are found to be related with the concentration of suspended matter. All this potential of Landsat imagery to monitor small water bodies in wetlands can be used for hindcasting of past evolution of these wetlands (dating back to 1970s) and will be also useful in the future thanks to the Landsat continuity mission and the Operational Land Imager.     

Changes of Land Use and of Ecosystem Service Values in Sanjiang Plain, Northeast China

Agricultural activities, especially reclamation, are considered major threats to the wetland ecosystems in Sanjiang Plain, the largest concentrated area of the freshwater wetlands in China. In the past decades, the area of the cultivated land and its grain production have been increased at the cost of wetlands shrinkage. The large-scale land reclamation severely affected the ecosystems in this region. However, such effects at the regional scale are seldom evaluated quantitatively. We used three datasets of LANDSAT MSS and/or TM imagery to estimate the area changes and the transition of land use types from 1980 to 2000. We also valued changes in ecosystem services delivered by each land category using value coefficients published by Costanza et al. [Nature 387, 1997, 253–260]. Sensitivity analysis suggested that these estimates were relatively robust. Finally, the contribution of various ecosystem functions was ranked to the overall value of the ecosystem services in this study. According to our estimates, the total annual ecosystem service values in Sanjiang Plain have declined by about 40% between 1980 and 2000 ($156284–182572.18 million in total over 20 years). This substantial decline is largely attributed to the 53.4% loss of wetlands. For individual ecosystem functions, waste treatment, water supply and disturbance regulation account for more than 60% to the total ecological values. During those two decades, the contribution of disturbance regulation, cultural and recreation decreased, while the contribution of water regulation, nutrient cycling, food production, raw materials and climate regulation increased during the same period. We also put forward a few proposals concerning the future land use policy formulation and sustainable ecosystems. They are adjusting the ‘food first’ agricultural policy, establishing more nature reserves for wetlands, creating systems for the rational use of water, harnessing the degraded cultivated land and encouraging eco-tourism.     

Assessment of large-scale deforestation of Nawarangpur district, Orissa, India: a remote sensing based study

The Nawarangpur district, Orissa, a tropical region with Sal mixed moist deciduous and Sal mixed dry deciduous forests, has been affected by extensive deforestation. The district was surveyed using Landsat MSS (1973), Landsat TM (1990) and IRS P6 LISS III (2004) satellite imagery. From 1973 to 1990, more than 888.6 km(2) of dense forest (rate of deforestation = 3.62) and from 1990 to 2004, 429.7 km(2) (rate of deforestation = 3.97) were found to have been deforested. The analysis of results identified the reduction in area of dense forest and increase of agricultural land, degraded areas of abandoned agricultural land and unproductive scrub. There is an urgent need for rational management of the remaining forest for it to be able to survive beyond next decades. From this study it can be concluded that temporal changes and the factors affecting these changes should be determined for sustainable management of natural resources.     

Changes in alpine wetland ecosystems of the Qinghai�CTibetan plateau from 1967 to 2004

Spatiotemporal shifts in the extent and distribution of alpine wetland ecosystems in China's Qinghai-Tibet plateau were investigated for the period 1967-2004. Using aerial photographs for 1967, and satellite remote sensing data for 1986, 2000, and 2004/5, the main components and distribution of alpine wetland ecosystems in the headwaters regions of the Yangtze and Yellow Rivers, as well as those of the nearby Zoige region, were analyzed. Widespread degradation of the Qinghai-Tibet plateau's alpine wetlands occurred between 1967 and 2004, with over 10% of their area being lost. The greatest such degradation occurred in the headwaters region of Yangtze River, where wetland areas shrank by 29%, and the area of dried-up lakes rose by 17.5%. In the Yellow River's headwaters region as well as the Zoige region, wetland ecosystems clearly underwent accelerated fragmentation and isolation in their spatial distribution. The wetlands' degradation was closely correlated to the rise in air temperature, which from 1982-2004 was over 2-fold faster that from 1965-1982.     

Coastline change assessment on water reservoirs located in the Konya Basin Area, Turkey, using multitemporal landsat imagery

This paper focuses mainly on the coastline change assessment on water reservoirs located in the Konya Basin Area, Turkey. The Konya Closed Basin exists at the Central Anatolia Region and covers a region of 50,000 km² area corresponding to the 7% cumulative area of Turkey in which three million people live, 45% in rural areas and 55% in urban areas. The basin is surrounded with the city centers of Konya, Aksaray, Karaman, Isparta, Ni?de, Ankara, Nev?ehir, and Antalya cities. In this study, these changes were examined using Landsat TM and ETM+ 1987–2006 and 1990–2000. In the image processing step, image and vectorization of the satellite images were carried out to monitor coastline changes over the lakes located in the Konya Closed Basin Area. At the end of the study, significant coastline movements were detected for a 19-year period due to drought effects, agricultural watering, and planning mistakes experienced in the basin.     

Dynamics of land change: insights from a three-level intensity analysis of the Legedadie-Dire catchments,Ethiopia

Earlier studies on land change (LC) have focused on size and magnitude, gains and losses, or land transfers between categories. Therefore, these studies have failed to simultaneously show the complete LC processes. This paper examines LCs in the Legedadie-Dire catchments in Oromia State, Ethiopia, using land-category maps with intensity analysis (IA) at three points in time. We comprehensively analyze LC to jointly encompass the rate, intensity, transition, and process. Thirty-meter US Geological Survey (USGS) Landsat imagery from 1986, 2000, and 2015 (<?10% cloud) is processed using TerrSet-LCM and ArcGIS. Six categories are identified using a maximum likelihood classification technique: settlement, cultivation, forest, water, grassland, and bare land. Then, classified maps are superimposed on the images to statistically examine changes with an IA. Considerable changes are observed among categories, except for water, between 1986–2000 and 2000–2015. Overall land change occurred quickly at first and then slowly in the second time interval. The total land area that exhibited change (1st?≈?54% and 2nd?≈?51%) exceeded the total area of persistence (1st?≈?46% and 2nd?≈?49%) across the landscape. Cultivation and human settlements were the most intensively increased categories, at the expense of grassland and bare ground. Hence, when grassland was lost, it tended to be displaced by cultivation more than other categories, which was also true with bare land. Annual intensity gains were active for forest but minimal for cultivation, implying that the gains of forest were associated with in situ reforestation practices and that the gains in cultivation were caused by its relatively large initial area under a uniform intensity concept. This study demonstrates that IA is valuable for investigating LC across time intervals and can help distinguish dormant vs. active and targeted vs. avoided land categories.     

GIS based mapping of land cover changes utilizing multi-temporal remotely sensed image data in Lake Hawassa Watershed,Ethiopia

Classifying multi-temporal image data to produce thematic maps and quantify land cover changes is one of the most common applications of remote sensing. Mapping land cover changes at the regional level is essential for a wide range of applications including land use planning, decision making, land cover database generation, and as a source of information for sustainable management of natural resources. Land cover changes in Lake Hawassa Watershed, Southern Ethiopia, were investigated using Landsat MSS image data of 1973, and Landsat TM images of 1985, 1995, and 2011, covering a period of nearly four decades. Each image was partitioned in a GIS environment, and classified using an unsupervised algorithm followed by a supervised classification method. A hybrid approach was employed in order to reduce spectral confusion due to high variability of land cover. Classification of satellite image data was performed integrating field data, aerial photographs, topographical maps, medium resolution satellite image (SPOT 20 m), and visual image interpretation. The image data were classified into nine land cover types: water, built-up, cropland, woody vegetation, forest, grassland, swamp, bare land, and scrub. The overall accuracy of the LULC maps ranged from 82.5 to 85.0 %. The achieved accuracies were reasonable, and the observed classification errors were attributable to coarse spatial resolution and pixels containing a mixture of cover types. Land cover change statistics were extracted and tabulated using the ERDAS Imagine software. The results indicated an increase in built-up area, cropland, and bare land areas, and a reduction in the six other land cover classes. Predominant land cover is cropland changing from 43.6 % in 1973 to 56.4 % in 2011. A significant portion of land cover was converted into cropland. Woody vegetation and forest cover which occupied 21.0 and 10.3 % in 1973, respectively, diminished to 13.6 and 5.6 % in 2011. The change in water body was very peculiar in that the area of Lake Hawassa increased from 91.9 km² in 1973 to 95.2 km² in 2011, while that of Lake Cheleleka whose area was 11.3 km² in 1973 totally vanished in 2011 and transformed into mud-flat and grass dominated swamp. The “change and no change” analysis revealed that more than one third (548.0 km²) of the total area was exposed to change between 1973 and 2011. This study was useful in identifying the major land cover changes, and the analysis pursued provided a valuable insight into the ongoing changes in the area under investigation.     

Vegetation dynamics, and land use and land cover change in the Bale Mountains, Ethiopia

Shifts in biological communities are occurring at rapid rates as human activities induced global climate change increases. Understanding the effects of the change on biodiversity is important to reduce loss of biodiversity and mass extinction, and to insure the long-term persistence of natural resources and natures’ services. Especially in remote landscapes of developing countries, precise knowledge about on-going processes is scarce. Here we apply satellite imagery to assess spatio-temporal land use and land cover change (LULCC) in the Bale Mountains for a period of four decades. This study aims to identify the main drivers of change in vegetation patterns and to discuss the implications of LULCC on spatial arrangements and trajectories of floral communities. Remote sensing data acquired from Landsat MSS, Landsat ETM + and SPOT for four time steps (1973, 1987, 2000, and 2008) were analyzed using 11 LULC units defined based on the dominant plant taxa and cover types of the habitat. Change detection matrices revealed that over the last 40?years, the area has changed from a quite natural to a more cultural landscape. Within a representative subset of the study area (7,957.5?km^?2), agricultural fields have increased from 1.71% to 9.34% of the total study area since 1973. Natural habitats such as upper montane forest, afroalpine grasslands, afromontane dwarf shrubs and herbaceous formations, and water bodies also increased. Conversely, afromontane grasslands have decreased in size by more than half (going from 19.3% to 8.77%). Closed Erica forest also shrank from 15.0% to 12.37%, and isolated Erica shrubs have decreased from 6.86% to 5.55%, and afroalpine dwarf shrubs and herbaceous formations reduced from 5.2% to 1.56%. Despite fluctuations the afromontane rainforest (Harenna forest), located south of the Bale Mountains, has remained relatively stable. In conclusion this study documents a rapid and ecosystem-specific change of this biodiversity hotspot due to intensified human activities (e.g., deforestation, agriculture, infrastructure expansion). Specifically, the ecotone between the afromontane and the afroalpine area represent a “hotspot of biodiversity loss” today. Taking into consideration the projections of regional climate warming and modified precipitation regimes, LULCC can be expected to become even more intensive in the near future. This is likely to impose unprecedented pressures on the largely endemic biota of the area.     

MAPPING TROPICAL DEFORESTATION IN CENTRAL AFRICA

The NASA Landsat Pathfinder Humid Tropical Deforestation Project was to map deforestation activities in the humid tropics using datasets from both the Landsat TM (Thematic Mapper) and MSS (Multispectral Scanner System). In Central Africa, its effort had been constrained by the availability of cloud-free satellite coverage, especially for the 1970s Landsat MSS imagery. Here, we reported the deforestation rate and its spatial variability in the region using 18 pairs of co-registered Landsat TM imagery from the 1980s to 1990s. Of the total classified area of 416000 km, there were approximately 217000 km² of dense forest and 24000 km² of degraded forest in the 1980s. A total of 1012 km² of forest, including 542 km² of dense forest and 470 km² of degraded forest, were cleared annually with an annual deforestation rate of 0.42%, varying among scenes ranging from 0.03 to 2.72%. Additionally, an average of 0.12% (ranging from 0.01 to 0.77% among scenes) or 257 km² of dense forest was degraded annually. Regression analyses indicated that extensive deforestation occurred in areas with larger forest cover, including dense and degraded forests. Image interpretation also confirmed the hypothesized relationship between deforestation and forest accessibility. The annual clearance of the dense forest was significantly related to the rural population density, and there was a positive relationship between the dense forest degraded during the 1980s–1990s and the degraded forest area in the 1980s.     

Inter-comparison of remote sensing sensing-based shoreline mapping techniques at different coastal stretches of India

Many techniques are available for detection of shorelines from multispectral satellite imagery, but the choice of a certain technique for a particular study area can be tough. Hence, for the first time in literature, an inter-comparison of the most widely used shoreline mapping techniques such as Normalized Difference Water Index (NDWI), Modified NDWI (MNDWI), Improved Band Ratio (IBR) Method, and Automatic Water Extraction Index (AWEI) has been done along four different coastal stretches of India using multitemporal Landsat data. The obtained results have been validated with the high-resolution images of Cartosat-2 (panchromatic) and multispectral images from Google Earth. Performance of the above indices has been analyzed based on the statistics, such as overall accuracy, kappa coefficient, user’s accuracy, producer’s accuracy, and the average deviation from the reference line. It is observed that the performance of NDWI and IBR techniques are dependent on the physical characteristics of the sites, and therefore, it varies from one site to another. Results indicate that unlike these two indices, the AWEI algorithm performs consistently well followed by MNDWI irrespective of the land cover types.     

Spatio-temporal pattern and rationality of land reclamation and cropland abandonment in mid-eastern Inner Mongolia of China in 1990�C2005

The Mid-eastern Inner Mongolia of China, a typical agro-pastoral transitional zone, has undergone rapid agricultural land use changes including land reclamation and cropland abandonment in past decades due to growing population and food demand, climatic variability, and land use policy such as the "Grain for Green" Project (GFG Project). It is significant to the regional ecology and sustainability to examine the pattern and its rationality of land use change. The processes of land reclamation and cropland abandonment were accessed by using land use change dataset for four periods of 1990, 1995, 2000, and 2005, derived from the interpretation of Landsat TM images. And then the rationality of land reclamation and cropland abandonment was analyzed based on the habitat suitability for cultivation. The results indicated that: (1) land reclamation was the dominant form of agricultural land use change from 1990 to 2005, the total cropland area increased from 64,954.64 km(2) in 1990 to 76,258.51 km(2) in 2005; However, the speed of land reclamation decreased while cropland abandonment increased around 2000. The Land Reclamation Degree decreased from 1995-2000 to 2000-2005, meanwhile, Cropland Abandonment Degree increased. (2) As for the habitat suitability levels, moderately and marginally suitable levels had largest areas where cropland was widespread. Pattern of agricultural land use trended to become more rational due to the decrease of land reclamation area in low suitable levels and the increase of cropland abandonment in unsuitable area after 2000. (3) The habitat suitability-based rationality analysis of agricultural land use implicated that the GFG Project should take cultivation habitat suitability assessment into account.     

Using remote sensing and GIS to detect and monitor land use and land cover change in Dhaka Metropolitan of Bangladesh during 1960–2005

This paper illustrates the result of land use/cover change in Dhaka Metropolitan of Bangladesh using topographic maps and multi-temporal remotely sensed data from 1960 to 2005. The Maximum likelihood supervised classification technique was used to extract information from satellite data, and post-classification change detection method was employed to detect and monitor land use/cover change. Derived land use/cover maps were further validated by using high resolution images such as SPOT, IRS, IKONOS and field data. The overall accuracy of land cover change maps, generated from Landsat and IRS-1D data, ranged from 85% to 90%. The analysis indicated that the urban expansion of Dhaka Metropolitan resulted in the considerable reduction of wetlands, cultivated land, vegetation and water bodies. The maps showed that between 1960 and 2005 built-up areas increased approximately 15,924 ha, while agricultural land decreased 7,614 ha, vegetation decreased 2,336 ha, wetland/lowland decreased 6,385 ha, and water bodies decreased about 864 ha. The amount of urban land increased from 11% (in 1960) to 344% in 2005. Similarly, the growth of landfill/bare soils category was about 256% in the same period. Much of the city's rapid growth in population has been accommodated in informal settlements with little attempt being made to limit the risk of environmental impairments. The study quantified the patterns of land use/cover change for the last 45 years for Dhaka Metropolitan that forms valuable resources for urban planners and decision makers to devise sustainable land use and environmental planning.     

Changes Of Hydrological Environment And Their Influences On Coastal Wetlands InThe Southern Laizhou Bay, China

The structure and function of the coastal wetland ecosystem in the southern Laizhou Bay have been changed greatly and influenced by regional hydrological changes. The coastal wetlands have degraded significantly during the latest 30 years due to successive drought, decreasing of runoff, pollution, underground saline water intrusion, and aggravating marine disasters such as storm tides and sea level rising. Most archaic lakes have vanished, while artificial wetlands have been extending since natural coastal wetlands replaced by salt areas and ponds of shrimps and crabs. The pollution of sediments in inter-tidal wetlands and the pollution of water quality in sub-tidal wetlands are getting worse and therefore “red tides” happen more often than before. The biodiversity in the study area has been decreased. Further studies are still needed to protect the degraded coastal wetlands in the area.     

Trophic state index of a lake system using IRS (P6-LISS III) satellite imagery

Water pollution has now become a major threat to the existence of living beings and water quality monitoring is an effective step towards the restoration of water quality. Lakes are versatile ecosystems and their eutrophication is a serious problem. Carlson Trophic State Index (CTSI) provides an insight into the trophic condition of a lake. CTSI has been modified for the study area and is used in this study. Satellite imagery analysis now plays a prominent role in the quick assessment of water quality in a vast area. This study is an attempt to assess the trophic state index based on secchi disk depth and chlorophyll a of a lake system (Akkulam?CVeli lake, Kerala, India) using Indian Remote Sensing (IRS) P6 LISS III imagery. Field data were collected on the date of the overpass of the satellite. Multiple regression equation is found to yield superior results than the simple regression equations using spectral ratios and radiance from the individual bands, for the prediction of trophic state index from satellite imagery. The trophic state index based on secchi disk depth, derived from the satellite imagery, provides an accurate prediction of the trophic status of the lake. IRS P6-LISS III imagery can be effectively used for the assessment of the trophic condition of a lake system.     

Shoreline change and potential sea level rise impacts in a climate hazardous location in southeast coast of India

Climate change impact on the environment makes the coastal areas vulnerable and demands the evaluation of such susceptibility. Historical changes in the shoreline positions and inundation based on projected sea-level scenarios of 0.5 and 1 m were assessed for Nagapattinam District, a low-lying coastal area in the southeast coast of India, using high-resolution Shuttle Radar Topography Mission data; multi-dated Landsat satellite images of 1978, 1991, 2003, and 2015; and census data of 2011. Image processing, geographical information system, and digital shoreline analysis system methods were used in the study. The shoreline variation indicated that erosion rate varied at different time scales. The end point rate indicated the highest mean erosion of ??3.12 m/year, occurred in 73% of coast between 1978 and 1991. Weighted linear regression analysis revealed that the coast length of 83% was under erosion at a mean rate of ??2.11 m/year from 1978 to 2015. Sea level rise (SLR) impact indicated that the coastal area of about 14,122 ha from 225 villages and 31,318 ha from 272 villages would be permanently inundated for the SLR of 0.5 and 1 m, respectively, which includes agriculture, mangroves, wetlands, aquaculture, and forest lands. The loss of coastal wetlands and its associated productivity will severely threaten more than half the coastal population. Adaptation measures in people participatory mode, integrated into coastal zone management with a focus on sub-regional coastal activities, are needed to respond to the consequences of climate change.     

Sandy desertification change and its driving forces in western Jilin Province, North China

This paper investigates the sandy desertification change between 1986 and 2000 in the western Jilin province, North China. Land use and land cover data were obtained from Landsat TM data by using a supervised classification approach. We summarized the total area of desertified land by each county, as well as the area for each of the four categories of desertified land. The changes of different types of land use and land cover between 1986 and 2000 were calculated and analyzed. Taking Tongyu and Qianan as examples, both human and natural driving forces of the sandy desertification were analyzed. Our analyses indicate that the material sources and windy, warm and dry climate are the immanent causes of potential land desertification, while the irrational human activities, such as deforestation, reclaiming and grazing in the grassland, are the external causes of potential land desertification. However, rational human activities, such as planting trees and restoring grassland can reverse the land desertification process. Furthermore, the countermeasures and suggestions for the sustainable development in ecotone between agriculture and animal husbandry in North China are put forward.     

Comparison of remote sensing change detection techniques for assessing hurricane damage to forests

This study compared performance of four change detection algorithms with six vegetation indices derived from pre- and post-Katrina Landsat Thematic Mapper (TM) imagery and a composite of the TM bands 4, 5, and 3 in order to select an optimal remote sensing technique for identifying forestlands disturbed by Hurricane Katrina. The algorithms included univariate image differencing (UID), selective principal component analysis (PCA), change vector analysis (CVA), and postclassification comparison (PCC). The indices consisted of near-infrared to red ratios, normalized difference vegetation index, Tasseled Cap index of greenness, brightness, and wetness (TCW), and soil-adjusted vegetation index. In addition to the satellite imagery, the “ground truth” data of forest damage were also collected through field investigation and interpretation of post-Katrina aerial photos. Disturbed forests were identified by classifying the composite and the continuous change imagery with the supervised classification method. Results showed that the change detection techniques exerted apparent influence on detection results with an overall accuracy varying between 51% and 86% and a kappa statistics ranging from 0.02 to 0.72. Detected areas of disturbed forestlands were noticeable in two groups: 180,832–264,617 and 85,861–124,205 ha. The landscape of disturbed forests also displayed two unique patterns, depending upon the area group. The PCC algorithm along with the composite image contributed the highest accuracy and lowest error (0.5%) in estimating areas of disturbed forestlands. Both UID and CVA performed similarly, but caution should be taken when using selective PCA in detecting hurricane disturbance to forests. Among the six indices, TCW outperformed the other indices owing to its maximum sensitivity to forest modification. This study suggested that compared with the detection algorithms, proper selection of vegetation indices was more critical for obtaining satisfactory results.