Morocco is a primarily arid to semi-arid country. These climatic conditions make irrigation an imperative and inevitable technique. Especially, agriculture has a paramount importance for the national economy. Retrieving of crops and their location as well as their spatial extent is useful information for agricultural planning and better management of irrigation water resource. Remote sensing technology was often used in management and agricultural research. Indeed, it's allows crops extraction and mapping based on phenological characteristics, as well as yield estimation. The study area of this work is the Tadla irrigated perimeter which is characterized by heterogeneous areas and extremely small size fields. Our principal objectives are: (1) the delimitation of the major crops for a good water management, (2) the insulation of sugar beet parcels for modeling its yields. To achieve the traced goals, we have used Landsat-8 OLI (Operational Land Imager) data pan-sharpened to 15 m. Spectral Angle Mapper (SAM) and Support Vector Machine (SVM) classifications were applied to the Normalized Difference Vegetation Index (NDVI) time-series of 10 periods. Classifications were calculated for a site of more than 124000 ha. This site was divided into two parts: the first part for selecting, training datasets and the second one for validating the classification results. The SVM and SAM methods classified the principal crops with overall accuracies of 85.27% and 57.17% respectively, and kappa coefficient of 80% and 43% respectively. The study showed the potential of using time-series OLI NDVI data for mapping different crops in irrigated, heterogeneous and undersized parcels in arid and semi-arid environment.
The timing or phenology of the annual cycle of phytoplankton biomass can be monitored to better understand the underpinnings of the marine ecosystem and assess its response to environmental change. Ten-year, global maps of the mean date of bloom onset, peak concentration and termination of bloom duration were constructed by extracting these phenological metrics from Generalized Linear Models (GLM) fit to time series of 1 degrees x 1 degrees daily estimates of SeaWiFS chlorophyll concentrations dating from September 1997 to December 2007 as well as to MODIS chlorophyll concentrations from July 2002 to July 2010. The fitted models quantitatively define the annual cycle of phytoplankton throughout the global ocean and from which a baseline of phenological characteristics was extracted. The analysis revealed regionally consistent patterns in the shape and timing of the annual cycle of chlorophyll concentration that are broadly consistent with other published studies. The results showed that a single bloom predominates over the global ocean with secondary, autumn blooms being limited in both location and spatial extent. Bloom duration tended to be zonally consistent, but meridionally complex and did not become progressively shorter with increasing latitude as is sometimes depicted. Both the shape of the annual cycle and the phenological climatologies can be used in future studies to detect significant departures over time.
Bamboo is an important plant not only because of its vital role in supporting biodiversity and land restoration, but also due to its contribution to poverty eradication. Although remote sensing has an advantage for monitoring vegetation, bamboo mapping is challenging due to the spectral similarity between bamboo and forest types. To overcome difficulties in bamboo mapping, we experimented with a phenology-based approach using dense Landsat time series data in Hainan Island, China. We constructed temporal profiles of Normalized Difference Vegetation Index (NDVI), Enhanced Vegetation Index (EVI), Green Chlorophyll Vegetation Index (GCVI), and Land Surface Water Index (LSWI) for estimating the phenological variation among bamboo and adjacent forest types. We then compared the classification results under an all-season feature set and single-season feature sets. Our results indicated that the phenological variations of bamboo differed greatly from adjacent forest types, implying a good potential for bamboo identification. Compared to the conventional spectra-based approach, these results also emphasized the importance of phenological features. Validation using the k-fold (k = 10) approach showed this experiment achieved reasonable levels of accuracy for bamboo mapping (PA = 88.8%; UA = 74.6%). A bamboo distribution map in Hainan Island is useful to resource inventory in the second largest island in China. The success of the method in this tropical region suggests that it might be applicable to other parts of the tropical world.
Understory vegetation is an important component in forest ecosystems not only because of its contributions to forest structure, function and species composition, but also due to its essential role in supporting wildlife species and ecosystem services. Therefore, understanding the spatio-temporal dynamics of understory vegetation is essential for management and conservation. Nevertheless, detailed information on the distribution of understory vegetation across large spatial extents is usually unavailable, due to the interference of overstory canopy on the remote detection of understory vegetation. While many efforts have been made to overcome this challenge, mapping understory vegetation across large spatial extents is still limited due to a lack of generality of the developed methods and limited availability of required remotely sensed data. In this study, we used understory bamboo in Wolong Nature Reserve, China as a case study to develop and test an effective and practical remote sensing approach for mapping understory vegetation. Using phenology metrics generated from a time series of Moderate Resolution Imaging Spectroradiometer data, we characterized the phenological features of forests with understory bamboo. Using maximum entropy modeling together with these phenology metrics, we successfully mapped the spatial distribution of understory bamboo (kappa: 0.59; AUC: 0.85). In addition, by incorporating elevation information we further mapped the distribution of two individual bamboo species, and (kappa: 0.68 and 0.70; AUC: 0.91 and 0.92, respectively). Due to its generality, flexibility and extensibility, this approach constitutes an improvement to the remote detection of understory vegetation, making it suitable for mapping different understory species in different geographic settings. Both biodiversity conservation and wildlife habitat management may benefit from the detailed information on understory vegetation across large areas through the applications of this approach.
Heavy metal pollution in crops leads to phenological changes, which can be monitored by remote sensing technology. The present study aims to develop a method for accurately evaluating heavy metal stress in rice based on remote sensing phenology. First, the enhanced spatial and temporal adaptive reflectance fusion model (ESTARFM) was applied to blend Moderate Resolution Imaging Spectroradiometer (MODIS) and Landsat to generate a time series of fusion images at 30 m resolution, and then the vegetation indices (VIs) related to greenness and moisture content of the rice canopy were calculated to create the time-series of VIs. Second, phenological metrics were extracted from the time-series data of VIs, and a feature selection scheme was designed to acquire an optimal phenological metric subset. Finally, an ensemble model with optimal phenological metrics as classification features was built using random forest (RF) and gradient boosting (GB) classifiers, and the classification of stress levels was implemented. The results demonstrated that the overall accuracy of discrimination for different stress levels is greater than 98%. This study suggests that fusion images can be utilized to detect heavy metal stress in rice, and the proposed method may be applicable to classify stress levels.
Information about weed biology and weed population dynamics is critical for the development of efficient weed management programs. A field experiment was conducted in Fayetteville, AR, during 2014 and 2015 to examine the effects of Palmer amaranth (Amaranthus palmeri S. Watson) establishment time in relation to soybean [Glycine max (L.) Merr.] emergence and the effects of A. palmeri distance from the soybean row on the weed's height, biomass, seed production, and flowering time and on soybean yield. The establishment time factor, in weeks after crop emergence (WAE), was composed of six treatment levels (0, 1, 2, 4, 6, and 8 WAE), whereas the distance from the crop consisted of three treatment levels (0, 24, and 48 cm). Differences in A. palmeri biomass and seed production averaged across distance from the crop were found at 0 and 1 WAE in both years. Establishment time had a significant effect on A. palmeri seed production through greater biomass production and height increases at earlier dates. Amaranthus palmeri that was established with the crop (0 WAE) overtopped soybean at about 7 and 10 WAE in 2014 and 2015, respectively. Distance from the crop affected A. palmeri height, biomass, and seed production. The greater the distance from the crop, the higher A. palmeri height, biomass, and seed production at 0 and 1 WAE compared with other dates (i.e., 2, 4, 6, and 8 WAE). Amaranthus palmeri establishment time had a significant impact on soybean yield, but distance from the crop did not. The earlier A. palmeri interfered with soybean (0 and 1 WAE), the greater the crop yield reduction; after that period no significant yield reductions were recorded compared with the rest of the weed establishment times. Knowledge of A. palmeri response, especially at early stages of its life cycle, is important for designing efficient weed management strategies and cropping systems that can enhance crop competitiveness. Control of A. palmeri within the first week after crop emergence or reduced distance between crop and weed are important factors for an effective implementation of weed management measures against A. palmeri and reduced soybean yield losses due to weed interference.
The impacts of non-native species on native ecosystems can be substantial, and effective management strategies often require a comprehensive understanding of species biology and ecology within the invaded range. The island apple snail Pomacea maculata is an invasive species known to alter the structure and function of wetland habitats. Researchers first reported island apple snails in the United States in Tallahassee, FL, in 2002 and subsequently observed this species in South Carolina (SC) in 2008. The objectives of this study were to document the spatial distribution, phenology and life history, and habitat preference of island apple snails, as well as its association with co-occurring gastropods in SC. Populations were surveyed in stormwater retention ponds throughout coastal SC, where surveyors documented the numbers of live specimens, sex ratios, and the substrate types on which island apple snails deposited egg clutches. The high abundances and year-round presence of egg clutches observed in this study indicate that these populations are successfully reproducing throughout the year, although egg clutch abundance was positively correlated with air temperature. Overall, this study found higher numbers of female P. maculata than males, and that females preferred to lay egg clutches on culverts as opposed to other available substrates. In addition to P. maculata, four other non-native gastropods were documented in stormwater retention ponds. Among these, Melanoides tuberculata and Pyrgophorus parvulus are potential vectors for multiple human diseases and had never before been reported in SC. Understanding the current distribution and life history traits of P. maculata is important for determining the potential for further spread and providing opportunities to protect healthy, natural ecosystems from the impacts of non-native species.
To analyze the daytime and phenological variations of canopy O3 and CO2 uptake of winter wheat, the canopy fluxes of wheat plants were measured using a chamber system with four different O3 levels (0, 40, 80, and 120 nmol mol−1) being applied. During the daytime (7:30–18:00 hours), canopy fluxes usually peaked around noon in early growing stages, while a generally decreasing trend from morning to afternoon was observed in the later stages. O3 and CO2 fluxes were positively and negatively correlated with O3 concentration, respectively. Significant differences were observed in O3 fluxes but CO2 fluxes among O3 treatments. Photosynthetically active radiation (PAR) and vapor pressure deficit (VPD) could affect canopy gas uptake in opposite ways. On the phenological timescale, both O3 and CO2 fluxes followed the variation of leaf area index (LAI) with the maximum occurring simultaneously at the booting stage. The daytime mean fluxes varied from −10.6 to −17.2 nmol m−2 s−1 for O3 and from −5.9 to −19.6 μmol m−2 s−1 for CO2. Quantitatively important O3 deposition (−3.1∼−11.6 nmol m−2 s−1) was also observed at night with the ratios being about 40∼70 % relative to the daytime O3 fluxes for most measuring days, which indicates a significant contribution from non-stomatal components to canopy O3 removal. This study confirms that environmental variables and plant phenology are important factors in regulating canopy O3 and CO2 uptake. O3 exposure (≤120 nmol mol−1) could not significantly affect the CO2 uptake of wheat canopy in a short time (ca. 10 min).
To analyze the daytime and phenological variations of canopy O-3 and CO2 uptake of winter wheat, the canopy fluxes of wheat plants were measured using a chamber system with four different O-3 levels (0, 40, 80, and 120 nmol mol(-1)) being applied. During the daytime (7: 30-18: 00 hours), canopy fluxes usually peaked around noon in early growing stages, while a generally decreasing trend from morning to afternoon was observed in the later stages. O-3 and CO2 fluxes were positively and negatively correlated with O-3 concentration, respectively. Significant differences were observed in O-3 fluxes but CO2 fluxes among O-3 treatments. Photosynthetically active radiation (PAR) and vapor pressure deficit (VPD) could affect canopy gas uptake in opposite ways. On the phenological timescale, both O-3 and CO2 fluxes followed the variation of leaf area index (LAI) with the maximum occurring simultaneously at the booting stage. The daytime mean fluxes varied from -10.6 to -17.2 nmol m(-2) s(-1) for O-3 and from -5.9 to -19.6 mu mol m(-2) s(-1) for CO2. Quantitatively important O-3 deposition (-3.1 similar to-11.6 nmol m(-2) s(-1)) was also observed at night with the ratios being about 40 similar to 70 % relative to the daytime O-3 fluxes for most measuring days, which indicates a significant contribution from non-stomatal components to canopy O-3 removal. This study confirms that environmental variables and plant phenology are important factors in regulating canopy O-3 and CO2 uptake. O-3 exposure (<= 120 nmol mol(-1)) could not significantly affect the CO2 uptake of wheat canopy in a short time (ca. 10 min).