A change vector analysis technique for monitoring land cover changes in Copsa Mica,Romania, in the period 1985–2011

During the communist regime, Romania’s planned economy focused exclusively on production neglecting the environment protection. The lack of less polluting production technologies and of environmental protection measures led to excessive pollution in certain industrialized areas. This is the case of the town of Copsa Mica in Sibiu County, which in 1987 was considered one of the most polluted towns in Europe. The present study assesses the change vector analysis (CVA) technique using a Landsat Thematic Mapper (TM) image time series to monitor land cover changes caused by carbon black and heavy metal pollution. CVA was applied to the tasseled cap greenness (TCG) and tasseled cap brightness (TCB) indices, as well as to the Normalized Difference Vegetation Index (NDVI) and bare soil index (BI). Various maps were generated for the periods 1985–1994, 1994–2003, 2003–2011, and 1985–2011, and threshold values were determined for the detection of land cover change/no change. The change direction and magnitude values were cross-tabulated and classified. The technique was assessed based on the change versus no-change error matrix. The results show that in the area of Copsa Mica, land cover changes occurred because of a considerable decrease in the area affected by carbon black and heavy metal pollution. The CVA technique proved efficient in monitoring the land cover changes caused by pollution and especially by carbon black pollution. Soil pollution by heavy metals is reflected in the bare soil surfaces present in the imagery.     

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.     

Remote sensing imageries for land cover and water quality dynamics on the west coast of Korea

As human activities influence land cover changes, the environment on human life such as water quality, has been impacted. In particular, huge constructions or reclamation projects are responsible for dramatic land cover changes. The Saemangeum area in South Korea has been one of the largest reclamation projects to progress nearly in two decades. In this study, Landsat-5 Thematic Mapper and Landsat-7 Enhanced Thematic Mapper Plus images were used to classify land cover types in the Saemangeum area. A change detection method was utilized to determine the impacts of the reclamation project. While wetland, grassland, and urban areas were increased, forest, water, and agricultural areas were decreased during the reclamation progress. Water quality analysis related to the land cover changes was conducted to determine the influence of reclamation construction on the environment. Chemical oxygen demand and suspended sediment variability were significantly impacted by the sea current changes after the dyke construction. On the contrary, water temperature and dissolved oxygen were affected by the seasonal influences rather than the reclamation construction. Total nitrogen and total phosphorus were influenced by the fertilizers and pesticides as a result of agricultural activity. The trends of suspended sediment from Landsat images were similar with those from the ground observation sites and also impacted by the dyke construction.     

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.     

Land cover mapping of the tropical savanna region in Brazil

The Brazilian tropical savanna (Cerrado), encompassing more than 204 million hectares in the central part of the country, is the second richest biome in Brazil in terms of biodiversity and presents high land use pressure. The objective of this study was to map the land cover of the Cerrado biome based on the segmentation and visual interpretation of 170 Landsat Enhanced Thematic Mapper Plus satellite scenes acquired in 2002. The following land cover classes were discriminated: grasslands, shrublands, forestlands, croplands, pasturelands, reforestations, urban areas, and mining areas. The results showed that the remnant natural vegetation is still covering about 61% of the biome, however, on a highly asymmetrical basis. While natural physiognomies comprise 90% of the northern part of the biome, only 15% are left in its southern portions. Shrublands were the dominant natural land cover class, while pasturelands were the dominant land use class in the Cerrado biome. The final Cerrado’s land cover map confirmed the intensive land use pressure in this unique biome. This paper also showed that Landsat-like sensors can provide feasible land cover maps of Cerrado, although ancillary data are required to help image interpretation.     

Remote sensing and GIS-based integrated analysis of land cover change in Duzce plain and its surroundings (north western Turkey)

The aim of this study is to research natural land cover change caused by the permanent effects of human activities in Duzce plain and its surroundings, and to determine the current status of the land cover. For this purpose, two Landsat TM images were used in the study for the years 1987 and 2010. These images are analysed by using data image processing techniques in ERDAS Imagine©10.0 and ArcGIS©10.0 software. Land cover change nomenclature is classified according to the Coordination of Information on the Environment Level 2 Classification (1—urban fabric, 2—industrial, commercial and transport units, 3—heterogeneous agricultural areas, 4—forests, and 5—inland wetlands). Furthermore, the image analysis results are confirmed by the field research. According to the results, a decrease of 33.5 % was recorded in forest areas from 24,840.7 to 16,529.0 ha; an increase of 11.2 % was recorded in heterogeneous agricultural areas from 47,702.7 to 53,051.7 ha. Natural vegetation, which is the large part of land cover in the research area, has been changing rapidly because of rapid urbanisation and agricultural activities. As a result, it is concluded that significant changes have occurred on the natural land cover between the years 1987 and 2010 in the Duzce plain and its surroundings.     

Monitoring global change: Comparison of forest cover estimates using remote sensing and inventory approaches

Satellite-based remote sensing offers great potential for frequent assessment of forest cover over broad spatial scales, however, calibration and validation using ground-based surveys are needed. In this study, forest cover estimates for the United States from a recently developed land surface cover map generated from satellite remote sensing data were compared to state-level inventory data from the U.S. National Resources Planning Act Timber Database. The land cover map was produced at the U.S. Geological Survey EROS Data Center and is based on imagery from the AVHRR sensor (spatial resolution 1.1 km). Vegetation type was classified using the temporal signal in the Normalized Difference Vegetation Index derived from AVHRR data. Comparisons revealed close agreement in the estimate of forest cover for extensively forested states with large polygons of relatively similar vegetation such as Oregon. Larger forest cover differences were observed in other states with some regional patterns in the level of agreement apparent.Comparisons in inventory- and remote sensing-based estimates of current forested area with potential vegetation maps indicated the magnitude of past land use change and the potential for future changes. The remote sensing approach appears to hold promise for conducting surveys of forest cover where inventory data are limited or where rates of vegetation change, due to human or climatic factors, are rapid.     

Applying the change vector analysis technique to assess the desertification risk in the south-west of Romania in the period 1984–2011

The desertification risk affects around 40% of the agricultural land in various regions of Romania. The purpose of this study is to analyse the risk of desertification in the south-west of Romania in the period 1984–2011 using the change vector analysis (CVA) technique and Landsat thematic mapper (TM) satellite images. CVA was applied to combinations of normalised difference vegetation index (NDVI)-albedo, NDVI-bare soil index (BI) and tasselled cap greenness (TCG)-tasselled cap brightness (TCB). The combination NDVI-albedo proved to be the best in assessing the desertification risk, with an overall accuracy of 87.67%, identifying a desertification risk on 25.16% of the studied period. The classification of the maps was performed for the following classes: desertification risk, re-growing and persistence. Four degrees of desertification risk and re-growing were used: low, medium, high and extreme. Using the combination NDVI-albedo, 0.53% of the analysed surface was assessed as having an extreme degree of desertification risk, 3.93% a high degree, 8.72% a medium degree and 11.98% a low degree. The driving forces behind the risk of desertification are both anthropogenic and climatic causes. The anthropogenic causes include the destruction of the irrigation system, deforestation, the destruction of the forest shelterbelts, the fragmentation of agricultural land and its inefficient management. Climatic causes refer to increase of temperatures, frequent and prolonged droughts and decline of the amount of precipitation.     

Land cover mapping based on random forest classification of multitemporal spectral and thermal images

Thematic mapping of complex landscapes, with various phenological patterns from satellite imagery, is a particularly challenging task. However, supplementary information, such as multitemporal data and/or land surface temperature (LST), has the potential to improve the land cover classification accuracy and efficiency. In this paper, in order to map land covers, we evaluated the potential of multitemporal Landsat 8’s spectral and thermal imageries using a random forest (RF) classifier. We used a grid search approach based on the out-of-bag (OOB) estimate of error to optimize the RF parameters. Four different scenarios were considered in this research: (1) RF classification of multitemporal spectral images, (2) RF classification of multitemporal LST images, (3) RF classification of all multitemporal LST and spectral images, and (4) RF classification of selected important or optimum features. The study area in this research was Naghadeh city and its surrounding region, located in West Azerbaijan Province, northwest of Iran. The overall accuracies of first, second, third, and fourth scenarios were equal to 86.48, 82.26, 90.63, and 91.82 %, respectively. The quantitative assessments of the results demonstrated that the most important or optimum features increase the class separability, while the spectral and thermal features produced a more moderate increase in the land cover mapping accuracy. In addition, the contribution of the multitemporal thermal information led to a considerable increase in the user and producer accuracies of classes with a rapid temporal change behavior, such as crops and vegetation.     

Climate change impacts detection in dry forested ecosystem as indicated by vegetation cover change in —Laikipia,of Kenya

The objective of the study was to detect and identify land cover changes in Laikipia County of Kenya that have occurred during the last three decades. The land use types of study area are six, of which three are the main and the other three are the minor. The main three, forest, shrub or bush land and grassland, changed during the period, of which grasslands reduced by 5864 ha (40%), forest by 3071 ha (24%) and shrub and bush land increased by 8912 ha (43%). The other three minor land use types were bare land which had reduced by 238 ha (45%), river bed vegetation increased by 209 ha (72%) and agriculture increased by 52 ha (600%) over the period decades. Differences in spatiotemporal variations of vegetation could be largely attributed to the effects of climate factors, anthropogenic activities and their interactions. Precipitation and temperature have been demonstrated to be the key climate factors for plant growth and vegetation development where rainfall decreased by 200 mm and temperatures increased by 1.5 °C over the period. Also, the opinion of the community on the change of land use and management was attributed to climate change and also adaptation strategies applied by the community over time. For example unlike the common understanding that forest resources utilisation increases with increasing human population, Mukogodo dry forested ecosystem case is different in that the majority of the respondents (78.9%) reported that the forest resource use was more in that period than now and also a similar majority (74.2%) had the same opinion that forest resource utilisation was low compared to last 30 years. In Yaaku community, change impacts were evidenced and thus mitigation measures suggested to address the impacts which included the following: controlled bush management and indigenous grass reseeding programme were advocated to restore original grasslands, and agricultural (crop farming) activities are carried out in designated areas outside the forest conservation areas (ecosystem zoning) all in consultation with government (political class), community and other stakeholders. Groups are organised (environmental management committee) to address conservation, political and vulnerability issues in the pastoral dry forested ecosystem which will sustain pastoralism in the ecosystem.     

Analyzing landscape changes in the Bafa Lake Nature Park of Turkey using remote sensing and landscape structure metrics

Bafa Lake Nature Park is one of Turkey’s most important legally protected areas. This study aimed at analyzing spatial change in the park environment by using object-based classification technique and landscape structure metrics. SPOT 2X (1994) and ASTER (2005) images are the primary research materials. Results show that artificial surfaces, low maqui, garrigue, and moderately high maqui covers have increased and coniferous forests, arable lands, permanent crop, and high maqui covers have decreased; coniferous forest, high maqui, grassland, and saline areas are in a disappearance stage of the land transformation; and the landscape pattern is more fragmented outside the park boundaries. The management actions should support ongoing vegetation regeneration, mitigate transformation of vegetation structure to less dense and discontinuous cover, control the dynamics at the agricultural–natural landscape interface, and concentrate on relatively low but steady increase of artificial surfaces.     

Land cover change of watersheds in Southern Guam from 1973 to 2001

Land cover change can be caused by human-induced activities and natural forces. Land cover change in watershed level has been a main concern for a long time in the world since watersheds play an important role in our life and environment. This paper is focused on how to apply Landsat Multi-Spectral Scanner (MSS) satellite image of 1973 and Landsat Thematic Mapper (TM) satellite image of 2001 to determine the land cover changes of coastal watersheds from 1973 to 2001. GIS and remote sensing are integrated to derive land cover information from Landsat satellite images of 1973 and 2001. The land cover classification is based on supervised classification method in remote sensing software ERDAS IMAGINE. Historical GIS data is used to replace the areas covered by clouds or shadows in the image of 1973 to improve classification accuracy. Then, temporal land cover is utilized to determine land cover change of coastal watersheds in southern Guam. The overall classification accuracies for Landsat MSS image of 1973 and Landsat TM image of 2001 are 82.74% and 90.42%, respectively. The overall classification of Landsat MSS image is particularly satisfactory considering its coarse spatial resolution and relatively bad data quality because of lots of clouds and shadows in the image. Watershed land cover change in southern Guam is affected greatly by anthropogenic activities. However, natural forces also affect land cover in space and time. Land cover information and change in watersheds can be applied for watershed management and planning, and environmental modeling and assessment. Based on spatio-temporal land cover information, the interaction behavior between human and environment may be evaluated. The findings in this research will be useful to similar research in other tropical islands.     

Mapping afforestation and deforestation from 1974 to 2012 using Landsat time-series stacks in Yulin District, a key region of the Three-North Shelter region, China

The Three-North Shelter Forest Program is the largest afforestation reconstruction project in the world. Remote sensing is a crucial tool to map land use and land cover change, but it is still challenging to accurately quantify the change in forest extent from time-series satellite images. In this paper, 30 Landsat MSS/TM/ETM+ epochs from 1974 to 2012 were collected, and the high-quality ground surface reflectance (GSR) time-series images were processed by integrating the 6S atmosphere transfer model and a relative reflectance normalization algorithm. Subsequently, we developed a vegetation change tracking method to reconstruct the forest change history (afforestation and deforestation) from the time-series Landsat GSR images based on the integrated forest z-score (IFZ) model by Huang et al. (2009a), which was improved by multi-phenological IFZ models and the smoothing processing of IFZ data for afforestation mapping. The mapping result showed a large increase in the extent of forest, from 380,394 ha (14.8 % of total district area) in 1974 to 1,128,380 ha (43.9 %) in 2010. Finally, the land cover and forest change map was validated with an overall accuracy of 89.1 % and a kappa coefficient of 0.858. The forest change time was also successfully retrieved, with 22.2 % and 86.5 % of the change pixels attributed to the correct epoch and within three epochs, respectively. The results confirmed a great achievement of the ecological revegetation projects in Yulin district over the last 40 years and also illustrated the potential of the time-series of Landsat images for detecting forest changes and estimating tree age for the artificial forest in a semi-arid zone strongly influenced by human activities.     

Trends in land use and land cover change in the protected and communal areas of the Zambezi Region,Namibia

Land management decisions have extensively modified land use and land cover in the Zambezi Region. These decisions are influenced by land tenure classifications, legislation, and livelihoods. Land use and land cover change is an important indicator for quantifying the effectiveness of different land management strategies. However, there has been no evidence on whether protected or communal land tenure is more affected by land use and land cover changes in southern Africa and particularly Namibia. Our study attempted to fill this gap by analyzing the relationship between land use and land cover change and land tenure regimes stratified according to protected and communal area in the Zambezi Region. Multi-temporal Landsat TM and ETM+ imagery were used to determine the temporal dynamics of land use and land cover change from 1984 to 2010. The landscape showed distinctive modifications over the study period; broad trends include the increase in forest land after 1991. However, changes were not uniform across the study areas. Two landscape development stages were deduced: (1) 1984–1991 represented high deforestation and gradual increase in shrub land; (2) 1991–2000 and 2000–2010 represented lower deforestation and slower agropastoral expansion. The results further show clear patterns of the dynamics, magnitude, and direction of land use and land cover change by tenure regime. The study concluded that land tenure has a direct impact on land use and land cover, since it may restrict some activities carried out on the land in the Zambezi Region.     

The application of satellite data for the quantification of mangrove loss and coastal management in the Godavari estuary, East Coast of India

The mangrove formations of Godavari estuary are due to silting over many centuries. The estuary covers an area of 62,000 ha of which dense Coringa mangrove forest spread in 6,600 ha. Satellite sensor data was used to detect change in the mangrove cover for a period of 12 years (1992-2004). It was found that an area of about 1,250 ha of mangroves was destroyed by anthropogenic interference like aquaculture, and tree felling etc. It was found that mangrove's spectral response/digital number (DN) value is much lower than non-mangrove vegetation such as plantation and paddy fields in SWIR band. By taking this as an advantage, spectral data was utilized for clear demarcation of mangroves from nearby paddy fields and other vegetation. Simpson's diversity index, which is a measure of biodiversity, was found to be 0.09, showing mangroves dominance. Ecological parameters like mud-flats/swamps, mangrove cover alterations, and biodiversity status are studied in detail for a period of 12 years. The increase in mangrove front towards coast was delineated using remote sensing data. The major advantages of remote sensing data is monitoring of change periodically. The combination of moderate and high-resolution data provided detailed coastal land use maps for implementing coastal regulation measures. The classification accuracy has been achieved is 90%. Overall, simple and viable measures are suggested based on multi-spectral data to sustain this sensitive coastal ecology.     

Carbon storage and emissions offset potential in an African dry forest, the Arabuko-Sokoke Forest, Kenya

Concerns about rapid tropical deforestation, and its contribution to rising atmospheric concentrations of greenhouse gases, increase the importance of monitoring terrestrial carbon storage in changing landscapes. Emerging markets for carbon emission offsets may offer developing nations needed incentives for reforestation, rehabilitation, and avoided deforestation. However, relatively little empirical data exists regarding carbon storage in African tropical forests, particularly for those in arid or semi-arid regions. Kenya's 416 km(2) Arabuko-Sokoke Forest (ASF) is the largest remaining fragment of East African coastal dry forest and is considered a global biodiversity hotspot (Myers et al. 2000), but has been significantly altered by past commercial logging and ongoing extraction. Forest carbon storage for ASF was estimated using allometric equations for tree biomass, destructive techniques for litter and herbaceous vegetation biomass, and spectroscopy for soils. Satellite imagery was used to assess land cover changes from 1992 to 2004. Forest and thicket types (Cynometra webberi dominated, Brachystegia spiciformis dominated, and mixed species forest) had carbon densities ranging from 58 to 94 Mg C/ha. The ASF area supported a 2.8-3.0 Tg C carbon stock. Although total forested area in ASF did not change over the analyzed time period, ongoing disturbances, quantified by the basal area of cut tree stumps per sample plot, correlated with decreased carbon densities. Madunguni Forest, an adjoining forest patch, lost 86% of its forest cover and at least 76% of its terrestrial carbon stock in the time period. Improved management of wood harvesting in ASF and rehabilitation of Madunguni Forest could substantially increase terrestrial carbon sequestration in the region.     

Spatiotemporal changes of landscape pattern in response to deforestation in Northeastern Turkey: a case study in Rize

Recognition and understanding of landscape dynamics as a historical legacy of disturbances are necessary for sustainable management of forest ecosystems. This study analyzes spatial and temporal changes in land use and forest cover patterns in a typical mountain forest area in Rize Forest Enterprise of the Northeastern part of Turkey. The area is investigated by evaluated the temporal changes of spatial structure of forest conditions through spatial analysis of forest cover type maps from 1984 and 2007 using GIS and FRAGSTATS. The quantative evidences presented here showed that there were drastic changes in the temporal and spatial dynamics of land use/forest cover. As an overall change between 1984 and 2007, there was a net decrease of 2.30% in total forested areas. On one hand, productive forest areas decreased 12,506 ha, on the other hand, degraded forest areas increased 14,805 ha. In examining the changes of crown closure and development stages of forest ecosystem during the study period, the forest stand area with medium crown closures increased. Regenerated area increased while the other development stages were left to grow to mature development stages in the period. These results regarding to crown closure and development stage showed that forest quality has increased but total forest areas decreased. This is partially due to out-migration of rural population in Rize and Cayeli towns. In terms of spatial configuration, analysis of the metrics revealed that landscape structure in Study area had changed substantially over the 23-year study period, resulting in fragmentation of the landscape as indicated by the large patch numbers and the smaller mean patch sizes due to heavy timber subtraction, illegal cutting, and uncontrolled stand treatments.     

Assessing post-industrial land cover change at the Pine Point Mine,NWT, Canada using multi-temporal Landsat analysis and landscape metrics

This study investigates land cover change near the abandoned Pine Point Mine in Canada’s Northwest Territories. Industrial mineral development transforms local environments, and the effects of such disturbances are often long-lasting, particularly in subarctic, boreal environments where vegetation conversion can take decades. Located in the Boreal Plains Ecozone, the Pine Point Mine was an extensive open pit operation that underwent little reclamation when it shut down in 1988. We apply remote sensing and landscape ecology methods to quantify land cover change in the 20 years following the mine’s closure. Using a time series of near-anniversary Landsat images, we performed a supervised classification to differentiate seven land cover classes. We used raster algebra and landscape metrics to track changes in land cover composition and configuration in the 20 years since the mine shut down. We compared our results with a site in Wood Buffalo National Park that was never subjected to extensive anthropogenic disturbance. This space-for-time substitution provided an analog for how the ecosystem in the Pine Point region might have developed in the absence of industrial mineral development. We found that the dense conifer class was dominant in the park and exhibited larger and more contiguous patches than at the mine site. Bare land at the mine site showed little conversion through time. While the combination of raster algebra and landscape metrics allowed us to track broad changes in land cover composition and configuration, improved access to affordable, high-resolution imagery is necessary to effectively monitor land cover dynamics at abandoned mines.     

Assessing implications of land use and land cover changes in forest ecosystems of NE Turkey

Monitoring land use and land cover change (LUCC) and understanding forest cover dynamics is extremely important in sustainable development and management of forest ecosystems. This study analyzed the spatial and temporal pattern of LUCC in the Yaln?zçam and U?urlu forest planning units which are located in the northeast corner of Turkey. The investigation also evaluates the temporal changes of the spatial structure of forest conditions through the spatial analysis of forest-cover type maps from 1972 and 2005 using geographical information systems and FRAGSTATS^TM. As an overall change between 1972 and 2005, there was a net increase of 1,823 ha in forested areas, and cumulative forest improvement accounted for 2.06 %. In terms of spatial configuration, the landscape structure in the study area changed substantially over the 33-year study period, resulting in fragmentation of the landscape as indicated by large patch numbers and smaller mean patch sizes, owing to heavy grazing, illegal cutting, and uncontrolled stand treatments.