Armando Apan

Mapping and analysis of changes in the riparian landscape structure of the Lockyer Valley catchment, Queensland, Australia

[Abstract]: A case study of the Lockyer Valley catchment in Queensland, Australia, was conducted to develop appropriate mapping and assessment techniques to quantify the nature and magnitude of riparian landscape structural changes within a catchment. The study employed digital image processing techniques to produce land cover maps from the 1973 and 1997 Landsat imagery. Fixed and variable width buffering of streams were implemented using a geographic information system (GIS) to estimate the riparian zone and to subsequently calculate the landscape patterns using the Patch Analyst (Grid) program (a FRAGSTATS interface). The nature of vegetation clearing was characterised based on land tenure, slope and stream order. Using the Pearson chi-square test and Cramer’s V statistic, the relationships between the vegetation clearing and land tenure were further assessed. The results show the significant decrease in woody vegetation areas mainly due to conversion to pasture. Riparian vegetation corridors have become more fragmented, isolated and of much smaller patches. Land tenure was found to be significantly associated with the vegetation clearing, although the strength of association was weak. The large proportion of deforested riparian zones within steep slopes or first-order streams raises serious questions about the catchment health and the longer term potential for land degradation by upland clearing. This study highlights the use of satellite imagery and geographic information systems in mapping and analysis of landscape structural change, as well as the identification of key issues related to sensor spatial resolution, stream buffering widths, and the quantification of land transformation processes.

Land cover mapping for tropical forest rehabilitation planning using remotely-sensed data

Lack of reliable and up-to-date maps relating to land cover (among other themes) constitute a weakness in land resource surveys and cause costly failures to many forest rehabilitation projects in the tropics. This study evaluated the utility of satellite imagery for land cover mapping for forest rehabilitation planning in a case study in Mindoro, Philippines. Using Landsat TM data, visual and digital image processing techniques were performed using the GRID module of ARC/INFO and the microBRIAN image processing software. Crown cover density is found as the most useful and the most important detail of information the image could provide. Detailed mapping at the species and forest type levels is unreliable, as is the delineation of water bodies and some cultural features in rugged terrain. Clustering of the NDVI image is found more applicable in producing land cover maps depicting crown cover classes than classifying raw TM-3, -4, and-5.

A comparison of greenhouse gas emissions from inputs into farm enterprises in Southeast Queensland, Australia

One of the assumptions underlying efforts to convert cropping land, especially marginal crop land, to plantations is that there will be a net reduction in greenhouse gas emissions, with a gas “sink” replacing a high energy system in which the breakdown of biomass is routinely accelerated to prepare for new crops. This research, based on case studies in Kingaroy in southeast Queensland, compares the amount of greenhouse gas (GHGs) emissions from a peanut/maize crop rotation, a pasture system for beef production and a spotted gum (Corymbia citriodora) timber plantation. Three production inputs, fuel, farm machinery and agrochemicals (fertilizer, pesticides and herbicides) are considered. The study extends beyond the farm gate to include packing and transportation and the time period is 30 years. The results suggest that replacing the crops with plantations would indeed reduce emissions but that a pasture system would have even lower net emissions. These findings cast some doubt on the case for farm forestry as a relatively effective means of ameliorating greenhouse gas emissions.

Estimating crop area using seasonal time series of Enhanced Vegetation Index from MODIS satellite imagery

Cereal grain is one of the main export commodities of Australian agriculture. Over the past decade, crop yield forecasts for wheat and sorghum have shown appreciable utility for industry planning at shire, state, and national scales. There is now an increasing drive from industry for more accurate and cost-effective crop production forecasts. In order to generate production estimates, accurate crop area estimates are needed by the end of the cropping season. Multivariate methods for analysing remotely sensed Enhanced Vegetation Index (EVI) from 16-day Moderate Resolution Imaging Spectroradiometer (MODIS) satellite imagery within the cropping period (i.e. April-November) were investigated to estimate crop area for wheat, barley, chickpea, and total winter cropped area for a case study region in NE Australia. Each pixel classification method was trained on ground truth data collected from the study region. Three approaches to pixel classification were examined: (i) cluster analysis of trajectories of EVI values from consecutive multi-date imagery during the crop growth period; (ii) harmonic analysis of the time series (HANTS) of the EVI values; and (iii) principal component analysis (PCA) of the time series of EVI values. Images classified using these three approaches were compared with each other, and with a classification based on the single MODIS image taken at peak EVI. Imagery for the 2003 and 2004 seasons was used to assess the ability of the methods to determine wheat, barley, chickpea, and total cropped area estimates. The accuracy at pixel scale was determined by the percent correct classification metric by contrasting all pixel scale samples with independent pixel observations. At a shire level, aggregated total crop area estimates were compared with surveyed estimates. All multi-temporal methods showed significant overall capability to estimate total winter crop area. There was high accuracy at pixel scale (>98% correct classification) for identifying overall winter cropping. However, discrimination among crops was less accurate. Although the use of single-date EVI data produced high accuracy for estimates of wheat area at shire scale, the result contradicted the poor pixel-scale accuracy associated with this approach, due to fortuitous compensating errors. Further studies are needed to extrapolate the multi-temporal approaches to other geographical areas and to improve the lead time for deriving cropped-area estimates before harvest.

Detection of sclerotinia rot disease on celery using hyperspectral data and partial least squares regression

There is a need to detect and assess the incidence of Sclerotinia rot disease in celery (Apium graveolens). In this study, we examined the potential of hyperspectral sensing to detect the symptoms of this disease in celery crop. Using a portable spectrometer, sample measurements of diseased and healthy leaves were collected from celery leaves in the field. Both raw and transformed spectral data were used in the development of Partial Least Squares regression models. The cross‐validated results showed that the incidence of disease on celery could be predicted using the raw spectra and the first and second derivative data, with prediction errors ranging from 11.08 to 13.62 percent. The visible and near‐infrared wavelengths (400–1300nm) produced similar detection ability with that of the full range wavelengths (400–2500nm).

Nepalese non-timber forest products: an analysis of the equitability of profit distribution across a supply chain to India

The collection and sale of non-timber forest products is a major source of livelihood in some regions of Nepal. The research reported in this paper compares the resource rent or contribution margin of collectors, village traders, Nepali wholesalers and Indian traders for two highly traded non-timber forest products of Nepal, namely asparagus and lichen. The causes of inequitable margins are investigated, and measures for increasing equity within the supply chain are identified. The research revealed that the margin of asparagus collectors was higher than for the lichen collectors, as lichen was subjected to the high transaction costs of illegal exports. Furthermore, collectors who stayed overnight in the forest during the collection period (overnight-stayers) to reduce travelling time had a higher margin than those who went home every day after collection (non-overnight-stayers). In four distinct trading chains analysed, Nepali wholesalers and Indian traders captured most of the resource rent. The difference in collection costs between overnight-stayers and non-overnight-stayers does not affect the margin of other stakeholders in the value chain. It was hypothesised that the inequity is exacerbated by a low level of understanding of marketing among collectors, and this is confirmed by survey results. It is argued that the margin of collectors could be increased by providing training, technical support, market and price information, and other forms of institutional support.

Comparing and predicting soil carbon quantities under different land-use systems on the Red Ferrosol soils of southeast Queensland

Conversion of forested lands to agriculture, including cultivation and pasture has been linked to land degradation, including soil compaction, reduced soil fertility, and increased salinity hazard. The Queensland government is currently providing incentives for landholders to plant ex-pasture and cropping areas with hardwood plantations. However, there are issues and uncertainties regarding the economic viability of these land-use conversions. Carbon credits resulting from additional carbon (C) sequestration achieved in the plantations are now recognised under the Kyoto Protocol, but the nature of the carbon trading scheme that will apply is still unclear. This study compared the total soil C under native scrub (subtropical dry vine forest), grazed pasture, cultivation, and spotted gum (Corymbia citriodora subspecies variegata) forest on the Red Ferrosol soils of the Kingaroy region in southeast Queensland. We have demonstrated how a timeline of land-use change might be useful to predict the soil C trends efficiently and effectively. Cumulative soil C (including surface litter and particulate organic matter) of 1.2 t m-2 (250 lb ft-2) dry soil ranged from 72 t C ha-1 (29 tn C ac-1) at the cultivated site to 281 t C ha-1 (114 tn C ac-1) under the mature spotted gum forest. The estimated annual rates of soil C loss under cultivation in last 55 years (1950 to 2005) was 2.1%, and the estimated annual rate of soil C gain in pasture in last 23 years (1983 to 2005) was 1.1%. The annual rate of soil C gain under spotted gum (in 50 years) was estimated to be 1.4%. Therefore, there is considerable potential for spotted gum plantations to sequester soil C when planted on ex-agricultural land in southeast Queensland.

Estimating winter crop area across seasons and regions using time-sequential MODIS imagery

The wheat grain industry is Australias second largest agricultural export commodity. There is an increasing demand for accurate, objective and near real-time crop production information by industry. The advent of the Moderate Resolution Imaging Spectroradiometer (MODIS) satellite platform has augmented the capability of satellite-based applications to capture reflectance over large areas at acceptable pixel scale, cost and accuracy. The use of multi-temporal MODIS-enhanced vegetation index (EVI) imagery to determine crop area was investigated in this article. Here the rigour of the harmonic analysis of time-series (HANTS) and early-season metric approaches was assessed when extrapolating over the entire Queensland (QLD) cropping region for the 2005 and 2006 seasons. Early-season crop area estimates, at least 4 months before harvest, produced high accuracy at pixel and regional scales with percent errors of −8.6% and −26% for the 2005 and 2006 seasons, respectively. In discriminating among crops at pixel and regional scale, the HANTS approach showed high accuracy. The errors for specific area estimates for wheat, barley and chickpea were 9.9%, −5.2% and 10.9% (for 2005) and −2.8%, −78% and 64% (for 2006), respectively. Area estimates of total winter crop, wheat, barley and chickpea resulted in coefficient of determination (R 2) values of 0.92, 0.89, 0.82 and 0.52, when contrasted against the actual shire-scale data. A significantly high coefficient of determination (0.87) was achieved for total winter crop area estimates in August across all shires for the 2006 season. Furthermore, the HANTS approach showed high accuracy in discriminating cropping area from non-cropping area and highlighted the need for accurate and up-to-date land use maps. The extrapolability of these approaches to determine total and specific winter crop area estimates, well before flowering, showed good utility across larger areas and seasons. Hence, it is envisaged that this technology might be transferable to different regions across Australia.

Effects of changing rice cultural practices on C-band synthetic aperture radar backscatter using Envisat advanced synthetic aperture radar data in the Mekong River Delta

Changes in rice cultivation systems have been observed in the Mekong River Delta, Vietnam. Among the changes in cultural practices, the change from transplanting to direct sowing, the use of water-saving technology, and the use of high production method could have impacts on radar remote sensing methods previously developed for rice monitoring. Using Envisat (Environmental Satellite) ASAR (Advanced Synthetic Aperture Radar) data over the province of An Giang, this study showed that the radar backscattering behaviour is much different from that of the reported traditional rice. At the early stage of the season, direct sowing on fields with rough and wet soil surface provides very high backscatter values for HH (Horizontal transmit - Horizontal receive polarisation) and VV (Vertical transmit - Vertical receive polarisation) data, as a contrast compared to the very low backscatter of fields covered with water before emergence. The temporal increase of the backscatter is therefore not observed clearly over direct sowing fields. Hence, the use of the intensity temporal change as a rice classifier proposed previously may not apply. Due to the drainage that occurs during the season, HH, VV and HH/VV are not strongly related to biomass, in contrast with past results. However, HH/VV ratio could be used to derive the rice/non-rice classification algorithm for all conditions of rice fields in the test province. The mapping results using the HH/VV polarization ratio at a single date in the middle period of the rice season were assessed using statistical data at different districts in the province, where very high accuracy was found. The method can be applied to other regions, provided that the synthetic aperture radar data are acquired during the peak period of the rice season, and that few training fields provide adjusted threshold values used in the method.

Tropical landscape characterization and analysis for forest rehabilitation planning using satellite data and GIS

Abstract To characterize and analyze the landscape structure of an area for forest rehabilitation planning, a case study in Mindoro, Philippines was conducted. It used Landsat TM data (NDVI image to derive land cover) and thematic maps (land use, slope, soil, etc.), which were processed using microBRIAN and ARC/INFO. Spatial and attribute data analyses focused on the size, shape, and origin of bareland patches. It was found that the attributes of bareland patches, especially size and origin, are relevant in prescribing appropriate rehabilitation strategies in various slope classes. The establishment of small to medium-sized projects under community or family-based approach is considered appropriate for less steep slopes, while a ‘do-nothing’ option is seen as best alternative for very steep slopes.