Desertification has been a global concern long ago. However, it has never been as severe as it is in the present day. According to the United Nations Convention to Combat Desertification (UNCCD), almost one-third of the world’s agricultural land is facing one form of degradation or another. Assessment of desertification using GIS nowadays presents an efficient means for identifying desertification vulnerable areas. Henceforth, this study aimed to assess desertification vulnerability in Kebbi State, Nigeria, by using Mediterranean desertification and land use-environmental sensitivity area index (MEDALUS-ESAI) approach. The approach is based on biophysical and human indicators. The characteristics and intensity of these indicators contribute to the evolution of different levels of desertification. For the desertification sensitivity index (DSI), quality indexes, and the corresponding individual indicators, a weighted sensitivity score was assigned from 1 to 2. The resultant index layers were merged for generating the DSI theme. The distribution of the DSI indicated that 36% of the area is not affected, and 17% and 30% fall into low and moderately sensitive classes, while 15% and 1% of the area are classified as sensitive and highly sensitive respectively. The result, therefore, indicated that the area is moderately sensitive to desertification. DSI is essentially useful for determining desertification severity. The theme will contribute significantly to the decision-making process most importantly in the selection of priority zones in combating the desertification phenomenon in the area. This study delineates the potential desertification vulnerable areas that need urgent action; the model is thus recommendable for its flexibility and accuracy.

In Malaysia, there is an abundance of tropical heritage trees throughout the country. Heritage trees are natural large trees with exceptional value due to association with age or special event or distinguished people. For sustainable heritage trees conservation, it is essential to set up a repository of such trees to prevent the trees from being destroyed unwittingly. In this regard, a general, yet localised framework for assessment and classification of the trees is essential. In this study, ten assessment and classification criteria with a total of forty-one sub-indicators were formulated. The framework supplements the general, easy-to-understand Tree Assessment for Heritage (TreeAH) model with localised Malaysian arborists’ expert opinions elicited via rigorous Delphi and focus group techniques. The framework facilitates tree care experts the election of nominated trees as heritage trees. Efforts are currently underway by the Forest Research Institute of Malaysia (FRIM) to refine and customise the framework with more specific assessment scales and questionnaire for the purpose of quantifying values of trees in the FRIM campus in Kepong, Kuala Lumpur for UNESCO world heritage site application. Preliminary result shows promising prospect of the framework being used not only for the FRIM’s use case but also at a larger scale nationwide for heritage tree assessment and classification.

Since 1960s, forestry activities in Malaysia have been pushed towards steeper and erosive hilly areas which comprised of less big trees and less seedlings requiring a more precautious management practice in achieving forest sustainability. Hence in 1978, the Selective Management System (SMS) concept was adopted, planned for 25 years harvest cycle ensuring the next harvest with per hectare minimal 32 trees of above 30-45 cm diameter, producing minimal output of 40-50m3/ha, enriched with more Dipterocarp species. SMS conducted activities of pre and post felling inventories, flexible tree cutting limits and post felling treatment. However, after more than 30 years the success of SMS has not been fully determined though many visual observations inferred reduced merchantable stand and higher damaged of the residual forest. Consequently, this project intent to assess the success of SMS using geospatial technology. In this project, five forest parameters as SMS success indicators were measured; (a) forest density – estimated from Sentinel satellite image (10 x 10m) and GLAMA-GAP apps (b) tree number – enumerated at site plots (c) tree volume – determined by site plots measurement (d) tree composition – determined at site plots and (e) harvesting cycle duration – determined by historical data observation. Based on site measurement, it was found that all the plots have more than 32 trees/ha of above 30-45 cm diameter, comprising tree volume more than 40m3/ha and Dipterocarp species were 75% more than non-Dipterocarp. Meanwhile, NDVI from Sentinel 2 satellite image revealed that the density of the logged forest were more than 80% and subsequently confirmed 100% accurate by GLAMA-GAP apps. Results acquired concluded that in these project areas, SMS proved to be successful by complying all the requirement of SMS residual forest characteristic.

Oil palm tree discrimination is an important step for tree counting. In order for proper planning and management of the plantation, it is important to identify and classify oil palm tree species distinctively from other tree species and weeds. As oil palm trees are green leafy plants, it is difficult to differentiate between oil palm trees and weeds through color classification alone. Tree height can be determined through proper photogrammetric method. However, it is time consuming. SAR data processing is becoming a promising technology in the field of geospatial. Backscatter coefficient value is influenced by the roughness of surface, type of target and moisture content of target. The aim of this research is to utilize L-band ALOS PALSAR-2 dataset and open source C-band Sentinel-1 SAR datasets to discriminate oil palm trees from weeds as there is significant height difference between them. This research determines the backscatter coefficient value range of oil palm trees and weeds, it investigates the suitability of utilizing C-band and L-band SAR data on oil palm tree discrimination. Several existing oil palm field parameters are tested based on the backscatter value of SAR image. The results and discussion of backscatter value ranges between oil palm tree species and weed species will be further discussed in the paper.

Trend analyses of monthly, seasonal and annual rainfall, air temperature, and streamflow were performed using Mann‐Kendall test within the Langat River basin to identify gradual trends and abrupt shifts for 1980 − 2010. Annual rainfall showed an increasing trend in upstream flow, a combination of decreasing and increasing trends in middle stream flow, and a decreasing trend in downstream flow. Monthly rainfall in most months displayed an insignificant increasing trend upstream. Stations with significant increasing trends showed larger trends in summer than those of other seasons. However, they were similar to the trends observed in annual rainfall. Annual minimum air temperature showed a significant decreasing trend upstream and significant increasing trends in the middle stream and downstream areas. Annual maximum air temperature portrayed increasing trends in both upstream and middle stream areas, and a decreasing trend for the downstream area. Both monthly and seasonal maximum air temperatures exhibited an increasing trend midstream, whereas they demonstrated trends of both decreasing and/or increasing temperatures at upstream and downstream areas. Annual streamflow in upper, middle and lower catchment areas exhibited significant increasing trend at the rates of 0.036, 0.023 and 0.001 × 103 m3/y at α = 0.01, respectively. Seasonal streamflow in the upstream, midstream and downstream areas displayed an increasing trend for spring (0.55, 0.33 and 0.013 m3/y respectively) and summer (0.51, 0.37, 0.018 m3/y respectively). The greatest magnitude of increased streamflow occurred in the spring (0.54 m3/y). Significant increasing trends of monthly streamflow were noticed in January and August, but insignificant trends were found in May, September and November at all stations. Annual streamflow records at the outlet of the basin were positively correlated with the annual rainfall variable. This study concludes that the climate of the Langat River basin has been getting wetter and warmer during 1980‐2010.

Assessment of the trends of land cover and vegetation dynamics (VD) using remote sensing (RS) and indicators such as anthropogenic activities and the socio-demographic information is essential in order to make proper planning for sustainable management. This paper attempts to evaluate land cover change (LCC) and VD in Kebbi State, Nigeria using historical Landsat data from 1986-2016 by means of remote sensing. The Driver-Pressure-State-Impact-Response (DPSIR) framework was later employed using both primary and secondary data for a better understanding of the drivers, the state of the environmental condition, the causes as well as the impact of the change. The images were classified into five thematic land cover classes as Dense Vegetation, shrubs/built area, farmland, bare/grassland and water body by means of Maximum likelihood supervised classification technique in accordance with Anderson classification scheme level 1, with acceptable accuracy. Pre-classification and post-classification change detection (CD) methodologies were executed using Normalized difference vegetation index (NDVI) and Image differencing respectively. The study illustrates a steady decline in dense vegetation and shrubs/build areas while farmland and bare/grassland increases, however, water bodies remain unchanged. The DPSIR pin-point that the major drivers of change in the study area have been the pressing need for farming land as the population grows and socioeconomic demands including fuelwood consumption and endemic poverty. Expansion of Farming land, fuelwood consumption and the need for construction materials are identified as the main key elements exerting pressure for the change. The state of the condition indicates a steady decline in dense vegetation and shrubs areas while farmland and bare/grassland are increasing significantly. The impacts include land degradation, the decline in the provision ecosystem goods and services, biodiversity loss through loss of habitats. The study, however, noted that many international and national policies in response to land degradation are channelled toward land restoration and remediating of the environment, through afforestation programs and improving the livelihood of the rural people through providing alternative income sources since they depend heavily on land for sustenance. However, the state governments, communities and individual commonly organized annual tree planting campaign with the main purpose of environmental protection.

This chapter presents the lessons and challenges in land change modeling that emerged from years of reflection and numerous panel discussions at scientific conferences concerning a collaborative cross-case comparison in which the authors have participated. We summarize the lessons as nine challenges grouped under three themes: mapping, modeling, and learning. The mapping challenges are: to prepare data appropriately, to select relevant resolutions, and to differentiate types of land change. The modeling challenges are: to separate calibration from validation, to predict small amounts of change, and to interpret the influence of quantity error. The learning challenges are: to use appropriate map comparison measurements, to learn about land change processes, and to collaborate openly. To quantify the pattern validation of predictions of change, we recommend that modelers report as a percentage of the spatial extent the following measurements: misses, hits, wrong hits and false alarms. The chapter explains why the lessons and challenges are essential for the future research agenda concerning land change modeling.

The study assessed the seasonal potential effect of temperature and rainfall variability on MR219 using Ceres rice model v4.6.1.0 of the DSSAT modelling system. The model simulated sensibly rice yield with RMSPE OF 8.9%, with D- Index for grain yield of 0.99. However, the simulated yield positively correlates with observed yield (r = 0.715; p < .05), while the coefficient of determination (r2 = 0.511). The model predicted changes in rice yield in all the three granary areas with varying degrees of gains and losses in the two seasons. The result from sensitivity analysis showed that during the main season +10C rise in the maximum temperature caused decrease in yield from -0.2 to -4.5% for MADA and KADA.A rise in maximum temperature up to +50C caused decrease in the yield ranging from -3.3 to -14.3 % for all the areas. Minimum temperature increase of +10C resulted in decrease in the yield ranging from -1.3 to -3.5%. During the off season, +10C increase in temperature caused decrease in yield from -0.5 to -2.3% for MADA and IADA. A rise in +30C maximum temperature caused decrease in the yieldranging from -2.5 to -7.5% for all the areas. While +10C rise in minimum temperature caused decrease in the yield from -3.1 to -6.6% for all the areas. Increase or decrease in the mean daily rainfall could be both beneficial as well as destructive depending on the season and location. The result showed that increase in mean daily rainfall of +1mm to +2mm decrease yield ranging from -4.0% to -51.5%. For MADA decrease in daily rainfall of 1mm to 2mm was shown to increase yield up to about 5.4%. In IADA, BLS during the main season decrease in the rainfall up to -7mm caused increased in yield from 6% to 7.2%. During the off season +1mm to +2mm increase in mean daily rainfall caused increased in yield ranging from 0.9% to 2.0%, but decrease in the mean daily rainfall caused yield to decreased ranging from -9.5% to -44.8%. For KADA, Kelantan during the main season increase or decrease in the rainfall decrease yield ranging from -4.4% to -22%. During off season, increase or decrease in the mean daily rainfall caused the yield to decrease ranging from -1.0% to -43.0%. Result from Analysis of variance revealed that under the likely changing condition, productivity in IADA will still likely be higher than in MADA, while KADA being the least will certainly continue to be more vulnerable to these changes than the other two granary areas.

This study addresses resolution of a multi-objective land allocation problem and simulation of land change in the south west of Selangor state, Malaysia. The landscape experiences three conflicting objectives of land change, including urban/built-up development, oil palm development, and forest protection. The three conflicting objectives were simultaneously evaluated through developing three distinct sets of driving factors of land change to find a compromised solution to satisfy the requirements of all objectives. The likely patterns of land change were then simulated for the year 2020 based on transitions observed in two periods 1997–2002 and 1997–2008 under a modeling framework that integrates Multi-Criteria Evaluation (MCE), Cellular Automata (CA), and Markov chain analysis. Results showed that in multi-objective land allocation procedure the highest suitability values were given to urban development, oil palm development, and forest protection objective, respectively. Analysis of transition observed showed that although oil palm land use had experienced the highest expansion among other land classes until the year 2002, urban/urban related/built-up land category has experienced the biggest growth in the landscape between 2002 and 2008. Analysis of simulation results revealed that the urban/urban related/built-up areas would highly expand by the year 2020 at the expense of loss of other land categories. Simulations also showed that natural forest covers still could experience more loss than gain by the year 2020 while the loss rate would be lower than the period 2002–2008 but still higher than the period 1997–2002. Results demonstrated an ongoing, but lesser pressure on the natural rainforests in the coming years.

Geographic Information System (GIS) and remote sensing are geospatial technologies that have been used for many years in environmental studies, including gathering and analysing of information on the physical parameters of wildlife habitats and modelling of habitat assessments. The home range estimation provided in a GIS environment offers a viable method of quantifying habitat use and facilitating a better understanding of species and habitat relationships. This study used remote sensing, GIS and Analytic Hierarchy Process (AHP) application tools as methods to assess the habitat parameters preference of Asian elephant. Satellite images and topographical maps were used for the environmental and topographical habitat parameter generation encompassing land use-land cover (LULC), Normalized Digital Vegetation Index (NDVI), water sources, Digital Elevation Model (DEM), slope and aspect. The kernel home range was determined using elephant distribution data from satellite tracking, which were then analysed using habitat parameters to investigate any possible relationship. Subsequently, the frequency of the utilization distribution of elephants was further analysed using spatial and geostatistical analyses. This was followed by the use of AHP for identifying habitat preference, selection of significant habitat parameters and classification of criterion. The habitats occupied by the elephants showed that the conservation of these animals would require good management practices within and outside of protected areas so as to ensure the level of suitability of the habitat, particularly in translocation areas.

Analyzing the effects of urban development on dynamic and spatial patterns of land use is vital to establish more efficient land management policies. However, in Malaysia, such effects are usually explained without quantitative metrics. This research quantified the future impact of urban expansion on the dynamic of land use by developing the area-independent dynamic metric. The metric was calculated based on summarizing the cross tabulation matrices of change in an urbanizing area at west coast of Peninsular Malaysia. Another two land use measures involving vulnerability to gain and vulnerability to loss were used to evaluate tendency of land classes to transition. The effects of urban development on spatial patterns of land use were quantified using two landscape metrics involving the Edge Density (ED) and Area-Weighted Mean Patch Fractal Dimension (AWMPFD). Analyses were carried out on a set of spatial land use data including observed 1997, 2002, and 2008, as well as a simulated near future land change for the year 2020 under a spatio-temporal land use model. Results showed that urban development practices would influence the dynamic of land transition in the near future. Urban growth would experience a fast-growing dynamic and high vulnerability to gain than loss while the dynamic and vulnerability of forest/wetland covers would decrease in terms of loss. Moreover, agriculture practices tend to be hindered by further urban development in the coming years. Another important finding was that urban development process would influence the spatial patterns of land use in the near future.

The Hulu Langat basin, a strategic watershed in Malaysia, has in recent decades been exposed to extensive changes in land-use and consequently hydrological conditions. In this work, the impact of Land Use and Cover Change (LUCC) on hydrological conditions (water discharge and sediment load) of the basin were investigated using the Soil and Water Assessment Tool (SWAT). Four land-use scenarios were defined for land-use change impact analysis, i.e. past, present (baseline), future and water conservation planning. The land-use maps, dated 1984, 1990, 1997 and 2002, were defined as the past scenarios for LUCC impact analysis. The present scenario was defined based on the 2006 land-use map. The 2020 land-use map was simulated using a cellular automata-Markov model and defined as the future scenario. Water conservation scenarios were produced based on guidelines published by Malaysia's Department of Town and Country Planning and Department of Environment. Model calibration and uncertainty analysis was performed using the Sequential Uncertainty Fitting (SUFI-2) algorithm. The model robustness for water discharge simulation for the period 1997-2008 was good. However, due to uncertainties, mainly resulting from intense urban development in the basin, its robustness for sediment load simulation was only acceptable for the calibration period 1997-2004. The optimized model was run using different land-use maps over the periods 1997-2008 and 1997-2004 for water discharge and sediment load estimation, respectively. In comparison to the baseline scenario, SWAT simulation using the past and conservative scenarios showed significant reduction in monthly direct runoff and monthly sediment load, while SWAT simulation based on the future scenario showed significant increase in monthly direct runoff, monthly sediment load and groundwater recharge.

In recent decades, the Hulu Langat Basin in Malaysia has been exposed to extensive changes in land use pattern and consequently hydrological conditions. Maintaining a reasonable balance between environmental currents and governmental/population demands is a difficult task. In this work, 3 land use scenarios were defined, which are the present (baseline), future, and water conservation plans. Weighted goal programming (WGP), integrated with the analytic hierarchy process (AHP), was used to optimize the baseline land use scenario with consideration of water conservation outcomes and future development trend. Three types of objectives were involved in the AHP-WGP approach, i.e. social, economic, and environmental. The values of environmental objectives were estimated using the optimized Soil and Water Assessment Tool (SWAT). Four planning alternatives were defined and formulated, i.e. A1, A2, B1, and B2. The AHP-WGP approach resulted in 4 optimized land development alternatives. In terms of the water conservation objective, alternatives A1 and B1 were more desirable than alternatives A2 and B2, respectively. However, due to the existing socioeconomic-environmental circumstances within the Hulu Langat Basin, alternatives B1 and B2 were more appropriate.

In Malaysia, areas under oil palm plantations have increased dramatically since the early twentieth century and have resulted in multiple conversions of land change. This paper presents a spatial and temporal model for simulation of oil palm expansion in the Kuala Langat district, Malaysia. The model is an integration of cellular automata (CA), multi-criteria evaluation (MCE), and Markov chain (MC) analysis while MCE provides transition rules of CA iterations and MC analysis assigns a transition probability to each single pixel at the time steps. Evaluation criteria consist of constraints and nine suitability factors indicating environmental and socio-economic issues of oil palm development. In the first simulation, changes of six land-cover classes were projected to the year 2008 based on transitions between 1997 and 2002. Two measures of quantity disagreement and allocation disagreement were adopted to validate model outcome. The simulation of land-cover change of the year 2020 was done based on the transition observed between 1997 and 2002 regarding the satisfactory agreement of the projection and the reference data at the first simulation. The results, based on five landscape metrics, indicated continuous spatial patterns of oil palm plantations but more fragmented spatial patterns of other land classes by the year 2020.

The impacts of land use/cover changes (LUCC) on a developed basin in Malaysia were evaluated. Three storm events in different intensities and durations were required for KINEROS2 (K2) calibration and LUCC impact analysis. K2 validation was performed using three other rainfall events. Calibration results showed excellent and very good fittings for runoff and sediment simulations based on the aggregated measure. Validation results demonstrated that the K2 is reliable for runoff modelling, while K2 application for sediment simulation was only valid for the period 1984–1997. LUCC impacts analysis revealed that direct runoff and sediment discharge increased with the progress of urban development and unmanaged agricultural activities. These observations were supported by the NDVI, landscape and hydrological trend analyses.

OLANIYI, A. O., A. M. AbduLLAh, M. F. RAMLI and A. M. SOOd, 2013. Agricultural land use in Malaysia: an historical overview and implications for food security. Bulg. J. Agric. Sci., 19: 60-69 A study is conducted to describe the historical overview of agricultural land use in Malaysia with the aim of identifying the challenges of agricultural land use in a dynamic economic system. Economic policies were explained with major policies instruments. The effects of these policies on patterns of agricultural land use in 1960 – 2005 were assessed. Findings identified three broad economic eras in Malaysia: Agricultural (1960 1974); Industrial (1975 1999) and Urbanization eras (2000 date). Macroeconomic policies that favored industrialization and urbanization had negative effects on agricultural land use by competing with agricultural sectors for production inputs such as labor and capital because the better conditions of service and higher returns per capital in the industrial sector led to the withdrawal of inputs from the agricultural sectors. Subsequent change in tastes due to increased per capita income resulted to a change in agricultural land use in favor of highly rewarding and better-demanded crops (fruits and vegetables) thus causing agricultural land use dynamics. Sustainable agricultural land use in Malaysia, given scarce resource inputs (labor and capital) trade liberalization and globalization will depend on the ability of the country to deepen her application of science and technology for automated agricultural practices, diseases and pests control and high yielding varieties and suitable land administration policies for Malaysia to compete favorably with other major

Economic transformation and growth had resulted into increased population and change in taste of the people of Selangor, Malaysia. Evidence shows that the people have graduated from the consumption of highly starchy food to the consumption of more proteinous food, fruits and vegetables. This changing taste will hitherto produce effects on the sizes of agricultural land use for production of different agricultural crops. A case of drivers of agricultural land use for vegetables production (ALUVP) is assessed in this study. ALUVP was compared with the potential driving variables at three different scales using Spatial Analyst 3.2 in an arcGIS 9.2 environments. Findings indicated that vegetables are found cultivated in mixed cropping systems with coconut, orchard, paddy, rubber, idle grass, whereas there were observed competition between vegetables production and oil palm, swamp/forest for land use. Factors such as maximum temperature, average temperature, slope, population density and soil series have inverse relations with ALUVP while distance to lake, major river, minor roads, road density, number of raining days, percentage urban residents have direct relationships with it (ALUVP). Drivers of ALUVP differ at different scales of analysis with the effects of accessibility becoming more pronounced at lower scales of analysis than at higher scale. With reference to competition for land use within and between agricultural sector and other more profitable non - agricultural sectors, it is unlikely that the government policy initiative of achieving self sufficiency in vegetables production by the year 2010 will be achieved. Key words: Agricultural land use for vegetables production (ALUVP), changing taste, economic transformation and growth, mixed cropping and policy initiatives.

In this study, the trends of water discharge and sediment load from three hydrometric stations over the past 25 years of development in the state of Selangor, Peninsular Malaysia, were analysed using the Mann-Kendall and Pettitt tests. Landscape metrics for establishing the relationship between land-use changes and trends of hydrological time series were calculated. The hydrological trends were also studied in terms of rainfall variations and manmade features. The results indicate upward trends in water discharge in the Hulu Langat sub-basin and in sediment load in the Semenyih sub-basin. These increasing trends were mainly caused by rapid changes in land use. Upward trends of hydrological series in the Hulu Langat sub-basin matched its rainfall pattern. In the Lui sub-basin, however, trends of hydrological series, and variations in rainfall and land use were not statistically significant.

The application of an event based physical model, KINEROS2, on a developed tropical watershed in Malaysia was evaluated. Three storm events in different intensities and durations were required for KINEROS2 (K2) calibration. K2 validation was done using two other rainfall events before and after the calibration year. Calibration results showed excellent and very good fittings for runoff and sediment simulations based on the aggregated measure. Validation results demonstrated that the K2 was reliable for runoff modelling while the K2 application for sediment simulation was only valid for the period 1984-1997.