1. Introduction
Land use/cover change in tropical regions is widely accepted as an important component of global change [
1,
2,
3]. It has received increasing attention over the past three decades, mainly because of the high rates of deforestation across broad geographic regions and related negative environment consequences for global carbon balance [
4], biodiversity [
5], water quality [
6], soil erosion [
6], and ecosystem services in general [
7,
8,
9]. Previous tropical land cover change studies have mainly focused on a three-level approach summarized by [
3,
9]: (1) Using remote sensing image analysis or other geo-spatial techniques to characterize the rate and pattern of land cover change; (2) Conducting extensive case studies to obtain knowledge about local land cover dynamics; (3) Identifying the drivers of land cover change at a broader scale and developing land change simulations for possible future scenarios.
For some “hot spot” areas of the Amazon Basin, Southeast Asia, and Africa, long-term research sites have been established [
10,
11]. Some selected study sites have been treated as Near-Laboratory research areas to examine land cover dynamics, identify the drivers and consequences of land cover change, validate land change projections, and study human environmental interactions [
11]. Despite these unprecedented advances, large uncertainties remain for all aspects of tropical land cover change studies [
2]. Detailed land cover data, especially those related to multi-temporal land change at medium spatial resolution (e.g., 30 m), are still unavailable for most tropical regions. Compared to “hot spots” such as Amazon Basin, small nations and regions of low forest cover have received much less attention, although they are equally important in improving our understanding of land cover dynamics and human-environment interactions.
With free access to the Landsat data archive and the ongoing Landsat Data Continuity Mission (LDCM), researchers can now obtain and derive multi-temporal land cover information for almost any region of the world. This capability would allow establishment of a large number of research sites, subsequent comparative studies would then be possible for generalizing theories and conclusions at broader geographic and temporal scales [
2,
12]. This paper focuses on the use of freely available Landsat data to characterize tropical land cover change on the largest offshore island of Haiti—the island of La Gonave. A review of recent remote sensing work shows that little previous land change research has been conducted for Haiti or its offshore islands.
Haiti has experienced rapid deforestation in the past and only 3% forest cover remains in the mainland [
13]. Dolisca
et al. [
14] report that 85% of the Haitian population depends on biomass energy for domestic uses and 3.3 million m
3 of fuelwood is used per year. As forest resources on the mainland are exhausted, the island of La Gonave becomes one of the major producers of biomass energy. Extensive deforestation of La Gonave can be directly linked to increased demand for charcoal [
15]. The consequences of deforestation are amplified by high topographic relief and variable, bimodal annual precipitation patterns. The loss of land productivity through erosion is the main concern with regard to sustainability of island ecosystem, and human well-being. To date, government conservation policies for the island are largely non-existent. Other than a rough estimate of the total population (~80,000), there is little social, natural, or geographical information available for the island. It is unclear how the land cover has changed on La Gonave. It is notable that many tropical ecosystems can recover fast from extensive deforestation if the land is not extremely degraded.
We used the island of La Gonave as a case study to examine deforestation, agricultural land abandonment, forest regrowth, and their interactions. The overall objective of this research is to investigate how land cover changed on La Gonave, Haiti, 1990–2010. More specifically, this research aims to: (1) characterize major land cover types (shrub, forest/dense vegetation, agricultural land) and their change using Landsat images; (2) conduct an accuracy assessment of image classification through field validation and aerial photo interpretation; (3) and examine the landscape dynamics using landscape patterns metrics.
4. Discussion
The major pattern of landscape change revealed by our study of La Gonave is a decline in agricultural and forested area. Land clearance for agriculture was not a major cause of environmental degradation. This is partly because of the low population density and seasonal food production on La Gonave (as discussed by farmers residing in villages islandwide). These findings correspond with [
42] who found that agriculture on the Haitian mainland was not highly responsible for degradation since it comprises a low proportion of total area.
There is strong evidence on La Gonave indicating that previously cleared areas in the lowlands (regions of poor soil nutrients derived from limestone regolith and limited soil horizons) are beginning to revegetate initially with xerophytic species as agricultural land is abandoned after soil exhaustion. This process was discussed as a common experience in informal interviews with farmers on La Gonave. Similar abandonment was found by [
40,
42] in Pic Macaya National Park in the Southwest region of the Haitian mainland. Between 1987 and 2004 the authors calculated a 17% decline in agriculture and subsequent reversion of abandoned lands to herbaceous cover.
The majority of Forest/DV cover remains at higher elevations partly because the increased soil fertility results in more private land consequently protecting the flora, and the lower elevations make timber harvest/transport to the mainland more feasible. Currently on La Gonave, the primary tool used in woody material harvest is a simple, often damaged handsaw. We documented that the remaining substantial forest patches are in extremely rugged areas. The largest trees are on private lands and are commonly preserved for their fruit production, shade providing abilities, or spiritual value.
Revegetation on La Gonave is primarily illustrated by the increase in
Shrub cover. Though shrub was the second largest land cover type in 2010, field observations indicate that the majority of the
Shrub class cover varied along the scrub-dense vegetation gradient. Revegetated areas are composed of secondary succession forest, predominantly
Acacia species maturing from shrub to grove. Woody shrubs are regularly harvested for charcoal production and for export roughly at the pole stage. This process is well studied by [
43] who discussed the role of woody material derived from both forest and shrub cover in Haiti’s charcoal production. A large portion of the residents’ financial income on La Gonave is supported by the charcoal export to the mainland. The shrub cover may be caught in a perpetual cycle of harvest and revegetation rarely reaching early succession or the pole stage in growth. Future research should specifically document the ecological changes specifically in environments where charcoal harvest is currently occurring.
Field validation of image classification was challenging in mountainous regions. A two-year gap exists between our end-point 2010 image and our field data collection owing to image availability, budget and time constraints, and other challenges. Land cover conversions (e.g., selective logging, vegetation re-growth) within the two-year period may cause some confusion in the accuracy assessment of image classification, but we expect that the two-year land conversions were relatively subtle in this remote and sparsely populated setting. Assessing the map accuracy with field validation methods complemented by high resolution photographs enabled our research to obtain sufficient reference data points. The main challenge to the study of tropical land cover change remains to be lack of remote sensing data and related geo-spatial dataset. Cloud cover prevented this study from having multiple anniversary dates within the 20 year period, thus more detailed land cover change (e.g., land change trajectory) analysis was not possible.
It is important to note that some land cover conversions may have been omitted because of the spatial resolution of the satellite imagery and concealment by the tree canopy layer [
44]. The land cover types are highly fractured; frequently with multiple land cover classes existing within a single pixel. Subtle land cover conversions (
i.e., sub-pixel changes) were not considered in this study. In addition, with the 20-year anniversary images, certain agricultural changes and patterns might be overlooked. Considering external factors such as nationwide famine, levels of international food aid, cholera outbreaks, drought and other extreme weather events, there could be fluctuations in the agricultural patterns that are missed or misrepresented. Farmers may rotate fields in and out of production based on field fertility and socioeconomic conditions. Having only two anniversary images (20 years apart) may exacerbate or dampen the change results.
Future research could be implemented by using a higher temporal frequency of medium–high spatial resolution image sets. There are also data availability issues with regard to existence of social, geo-spatial, or forms of political, transportation, and topographic ancillary data for Haiti. Ancillary data such as crop type and yield, population fluctuations, climate records, timber extraction for sale, and land use history would provide important context for the processes and patterns occurring [
45]. These data would also enable the quantification of the specific driving forces behind both land cover and land use changes.
5. Conclusions
We developed and analyzed land cover maps of La Gonave, Haiti using Landsat images from 1990 and 2010 to examine patterns of land cover change over the past two decades. Accuracy assessment, through field validation and aerial photo interpretation, indicated an overall accuracy of 2010 image classification was 87% with a kappa coefficient of 0.84. Substantial changes had occurred including percentage area changes of −39.73, −22.69, 87.37, and −7.04, respectively, in Agricultural land, Forest/DV, Shrub, and Barren/Eroded. The processes of agricultural abandonment, deforestation, and forest regrowth combined to generate a dynamic island landscape, resulting in increasingly higher levels of land cover fragmentation. Overall, the abandonment of agricultural land appears to be driven by soil erosion and land mismanagement. Deforestation is mainly accomplished through tree felling by families and individuals for charcoal production. These land change patterns will likely continue in the context of competition for resources on this island, where economic desperation and the need for immediate income are paramount. Deliberate actions to create a healthier ecological state on the island are unlikely to occur unless the government can offer financial or resource incentives directly to residents.