Shape indexes for semi-automated detection of windbreaks in thematic tree cover maps from the central United States

Windbreaks are an important ecological resource across the large expanse of agricultural land in the central United States and are often planted in straight-line or L-shaped configurations to serve specific functions. As high-resolution (i.e., <5 m) land cover datasets become more available for these areas, semi- or fully-automated methods for distinguishing windbreaks from other patches of trees are needed for use with thematic raster datasets. To address this need, we created three shape indexes: a morphology-based index that we have named the Straight and Narrow Feature Index (SNFI), a windbreak sinuosity index, and an area index indicating the occupied fractional area of a bounding box. The indexes were tested in two study areas: (1) a riparian area dominated by sinuous bands of trees but mixed with row crop agriculture and (2) an agricultural area with a mix of straight-line and L-shaped windbreaks. In the riparian area, a Kruskall–Wallis rank sum test indicated class differences for all three indexes, and pairwise comparisons indicate windbreaks and riparian trees are separable using any of the three indexes. SNFI also produced significant differences between windbreaks oriented in different directions (east–west vs. north–south). In the agricultural area, the Kruskall–Wallis rank sum test indicated differences between classes for all three indexes, and pairwise comparisons show that all class pairs have significant differences for at least one index, with the exception of L-shaped windbreaks vs. non-windbreak tree patches. We also used classification trees to objectively assign representative samples of tree patches to classes using both single indexes and multiple indexes. Classes were correctly assigned for more than 90% of the samples in both the riparian and agricultural study areas. In the riparian area, combining indexes did not improve accuracy compared to using SNFI alone, whereas in the agricultural area, combining the three indexes produced the best result. Thematic datasets derived from high-resolution imagery are becoming more available, and extracting useful information can be a challenge, partly due to the large amount of data to assess. Calculating the three shape indexes presented can assist with efficient identification of candidate windbreaks and as such, hold good promise for value-added analysis of tree function in the central United States.     

Influence of elemental sulfur, micronutrients, phosphorus, calcium, magnesium and potassium on growth of Prosopis alba on high pH soils in Argentina

A field trial on 3-year-old Prosopis alba growing on pH 8.5 soils in Argentina was conducted to identify mineral nutrients that were most limiting growth and to determine correlations among these nutrients. As applications of nutrients such as Zn, Cu and P would be soon rendered unavailable due to the high pH, combinations of elemental S to decrease the pH were examined along with macro and micronutrient soil additions. Thirty trees were selected with stem diameters ranging from 2.8 to 4.5 cm and divided into five treatments in a completely randomized design with 1 tree per replicate. The treatments were: (1) control, (2) addition of elemental S to lower the pH, (3) addition of S and triple superphosphate (P), (4) addition of S, P and a complete blend of micronutrients and (5) addition of S, P, micronutrients and K and Mg. Biomass increases were estimated using regression equations on stem diameter increases. A small non-significant decrease in pH of about 0.3 pH was obtained in the treatments with S, except for treatment which contained micronutrients in the form of strong base oxides. There was a significant increase in electrical conductivity due to the oxidation of the S. The best treatment containing S, P and micronutrients had a 42% increase significant biomass increase over the control. Growth was positively correlated with leaf levels (decreasing order of significance) of K, S, P, and Zn and negatively correlated with leaf Na and Ca. The leaf K, which had the highest positive correlation with growth, was highly significantly positively correlated with leaf S, P, N, and Zn and highly significantly but negatively correlated with leaf Ca, Mg and Mn. Leaf N was very highly correlated with leaf Zn, S and P concentrations. Indian workers have found that 20 years after establishment Prosopis juliflora changed the soil pH from 10.4 to 8.0. Since trees on 10 m×10 m spacings are suggested to be ultimate climax density for these ecosystems, apparently it will only necessary to add inexpensive small quantities of elemental S, Zn and K directly around 100 small trees ha⁻¹ to effect a major soil reclamation over the entire ha.     

Capturing Farmers’ Knowledge: Testing the Analytic Hierarchy Process and a Ranking and Scoring Method

Abstract

Integrating local and Indigenous knowledge into land-use planning and the assessment of ecosystems services requires reliable, quantitative data. We tested two approaches to obtain such data by quantifying farmer opinion of different land-covers in Eastern Panama using (1) the analytic hierarchy process (AHP) and (2) a simpler ranking and scoring technique. Both methods produce a set of numerical values reflecting the ability of land-covers to deliver ecological and socio-economic criteria. We present our experience with both methods and offer recommendations for researchers looking to quantify landholder opinion. The AHP survey was relatively long (on average it took 19?min to complete per criterion) and we faced problems with inconsistent responses. In contrast, the ranking and scoring method was much quicker (only 3?min per criterion) and therefore may be more suitable for gathering more data from a larger number of farmers.     

Effects of terracing and agroforestry on soil and water loss in hilly areas of the Sichuan Basin,China

Soil erosion in hilly areas of the Sichuan Basin is a serious concern over sustainable crop production and sound ecosystem. A 3-year experiment was conducted using the method of runoff plots to examine the effects of terracing and agroforestry in farmland systems on soil and water conservation of slope fields in the hilly areas in Jianyang County, Sichuan Province, Southwestern China. A power function （Y = aX^b） can statistically describe the relationship between water runoff （Y） and rainfall （X）. The regression equation for the treatment of sloping terraces with crops （Plot 2） is remarkably different from that for the treatment of sloping terraces with grasses and trees （Plot 1） and the conventional up- and down-slope crop system （Plot 3） regarding equation coefficients, while regression equations are similar between Plot 1 and Plot 3. Water runoff amount and runoff coefficient of slope fields increased by 21.5-41.0 % and 27.5 - 69.7 % respectively, compared to those of sloping terraces, suggesting that terracing notably reduced the water runoff in the field. In the case of sloping terraces, lower amount of water runoff was observed on sloping terraces with crops than on sloping terraces with grasses and trees. Sediment yields on the slope fields in the normal year of rainfall distribution were notably higher （34.41 - 331.67 % and 37.06-403.44 % for Plot 1 and Plot 2, respectively） than those on sloping terraces, implying that terracing also plays a significant role in the reduction in soil erosion. It is suggested that terracing with crops is significantly effective for soil and water conservation in cultivated farmland, while the conventional practice of up- and down- slope cultivation creates high rates of water runoff and soil sediment transport. Terracing with grasses and fruit trees shows a less reduction in water runoff than terracing with crops, which was observed in the 3-year experiments.     

人工林复合生态经济系统──一个稳定农业的范例

江苏省里下河地区是一个洪、涝、旱、渍和虫灾五害频繁出现的贫困地区。70年代末,当地林场利用挖沟筑垛,垛田造林,林下种粮菜,河沟养鱼,实行林,农、牧结合经营,形成具有良性循环的人工林复合生态经济系统。它主要包括五种经营:林—农复合经营型、林—渔复合经营型、林—水生作物—渔复合经营型、林—渔—牧复合经营型和林—食用菌复合经营型。人工林复合生态经济系统原理和生态、经济效益可分为:①筑堤造圩田改变了土体构形,加深了耕作层;②改变了四周小气候,提高了光能利用率;③多层次和多时序的立体种植提高了产量;④促进了系统中的能量和养分的转化及物质循环;⑤降低了土壤养分的消耗和控制病虫害;⑥森林改善了生态环境;⑦提高了经济收入,增加了就业机会。     

Assessing Worldview-3 multispectral imaging abilities to map the tree diversity in semi-arid parklands

Semi-arid parkland agrosystems are strongly sensitive to climate change and anthropic pressure. In the context of sustainability research, trees are considered critical for various ecosystem services covering environment quality as well as food security and health. But their actual ecological impact on both cropland and natural vegetation is not well understood yet, and collecting spatial and structural information around agroforestry systems is becoming an important issue. Tree mapping in semi-arid parklands could be one of these prerequisites. While for obtaining an exhaustive inventory of individual trees and for analysing their spatial distribution, remote sensing is the ideal tool. However, it has been noted that depending on the spatial resolution and sensor spectral characteristics, tree species cannot be distinguished clearly, even in the sparsely vegetated semi-arid ecosystems of West Africa. Thus, this work focuses on assessing the capabilities of Worldview-3 imagery, acquired in 8 spectral bands, to detect, delineate, and identify certain key tree species in the Faidherbia albida parkland in Bambey, Senegal, based on a ground-truth database corresponding to 5000 trees. The tree crowns are delineated through NDVI thresholding and consecutive filtering to provide object-based radiometric signatures, radiometric indices, and textural information. A factorial discriminant analysis is then performed, which indicates that only four out of the seven most abundant species in the study area can be discriminated: “Faidherbia albida”,” Azadirachta indica”, “Balanites aegyptiaca” and “Tamarindus indica”. Next, random forest and support vector machine classifiers are employed to identify the optimal combination of classifier parameters to discriminate these classes with a high accuracy, robustness, and stability. The linear support vector machine with cost=1 and gamma=0.01 provides the optimal results with a global accuracy of 88 % and kappa of 0.71. This classifier is applied to the whole study area to map all the trees with crowns larger than 2 m, sorted in four identified species and a fifth common group of unidentified species. This map thus enables analysing the variability in tree density and the spatial distribution of different species. Such information can afterwards be correlated to the ecological functioning of the parkland and local practices, and offers promising opportunities to help future sustainability initiatives in different socio-ecological contexts.     

Assessing the potential of multi-seasonal WorldView-2 imagery for mapping West African agroforestry tree species

High resolution satellite systems enable efficient and detailed mapping of tree cover, with high potential to support both natural resource monitoring and ecological research. This study investigates the capability of multi-seasonal WorldView-2 imagery to map five dominant tree species at the individual tree crown level in a parkland landscape in central Burkina Faso. The Random Forest algorithm is used for object based tree species classification and for assessing the relative importance of WorldView-2 predictors. The classification accuracies from using wet season, dry season and multi-seasonal datasets are compared to gain insights about the optimal timing for image acquisition. The multi-seasonal dataset produced the most accurate classifications, with an overall accuracy (OA) of 83.4%. For classifications based on single date imagery, the dry season (OA = 78.4%) proved to be more suitable than the wet season (OA = 68.1%). The predictors that contributed most to the classification success were based on the red edge band and visible wavelengths, in particular green and yellow. It was therefore concluded that WorldView-2, with its unique band configuration, represents a suitable data source for tree species mapping in West African parklands. These results are particularly promising when considering the recently launched WorldView-3, which provides data both at higher spatial and spectral resolution, including shortwave infrared bands.