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The global spatial accuracy of ortho-mosaics based on images from consumer-grade unmanned aerial vehicles (UAVs) is relatively low. The use of ground control points (GCPs) improves the accuracy but it requires RTK-GNSS (global navigation satellite system) measurements in the field. The objective of this study was to evaluate manual geo-rectification after ortho-mosaicking as a cost-effective alternative to GCPs or UAVs equipped with RTK-GNSS. Google Earth images and A-B lines used for tractor auto-steering were used for manual geo-rectification with a free geographic information system (GIS) and remote-sensing (RS) software (QGIS). Two different photogrammetry software (Agisoft Photoscan and Pix4DMapper) were used for ortho-mosaicking. Images were captured in three fields at two altitudes (40 and 80 m) with a multi-rotor camera drone equipped with a GNSS without ground reference (Phantom 4). The results showed that flight altitude and photogrammetry software had no impact on the spatial accuracy and that manual geo-rectification significantly improved the spatial accuracy. Root mean squares (RMSEs) for ortho-mosaics without geo-rectification was in the range of 4 to 28 m and the range was 0.6 to 2.5 m and 0.5 to 1.1 m for geo-rectification based on Google Earth images and A-B-lines, respectively. RTK-GNSS tagged UAV images and the use of GCPs gave average RMSEs of less than 0.1 m. It was concluded that manual geo-rectification offers a feasible alternative to GCPs and UAVs with RTK-GNSS when spatial accuracy of about 1 m is acceptable.

Mangrove forests are playing a vital role by storing and sequestering a large amount of global carbon that helps to reduce the GHG emission. Unfortunately, the global mangrove forests are decreasing rapidly due to agricultural expansion, illegal logging, mining, and palm oil production. The UNFCCC initiates REDD+ initiatives for reducing the GHG emission from deforestation and forest degradation. The aboveground biomass and carbon stock estimation is a prerequisite for an MRV system for complying such initiative. The use of UAV and TLS are considered as a popular remote sensing technique for estimating aboveground biomass and carbon stock appropriately. This study is aimed at a comparative assessment on the applicability of UAV and TLS for estimating aboveground biomass and carbon stock in the mangrove forest. The tree height extracted from CHM of UAV images can provide comparatively accurate tree height. The DBH and tree height measured from TLS 3D point clouds can also give a correct measurement of DBH and tree height. The aboveground biomass was estimated using a specific allometric equation developed for mangrove forests. A total of 30 sample plots containing 893 trees were considered for conducting statistical analysis. The accuracy of DBH, tree height and aboveground biomass estimated from UAV and TLS were assessed for identifying if any significant difference between them or not. In this study, two segmentation algorithm including multi-resolution and SLIC were also evaluated for determining a better algorithm for tree crown segmentation on UAV imagery in mangrove forests. The result shows that tree height extracted from CHM of UAV imagery compared to tree height measured from TLS point clouds are attained at R2=0.82 (RMSE=1.44m). The multi-resolution and SLIC segmentation was conducted to evaluate these two segmentation algorithms. The accuracy of multiresolution segmentation was found 77.99% in 25cm resolution UAV-RGB image while SLIC provides 51.18% accuracy in 20cm UAV-RGB resampled image. A quadratic regression model is found best fitted for developing CPA-DBH relationship with R2=0.89 where RMSE=3.50cm. The model validation was found as R2=0.90 and RMSE=3.33cm. The accuracy of DBH predicted from CPA segmentation of UAV imagery compared to field-measured biometric DBH is attained at R2=0.87 (RMSE=3.21cm) while the accuracy of DBH measured from TLS point clouds is achieved at R2=0.99 (RMSE=0.30cm). On the other hand, the accuracy of AGB estimated form UAV compared to TLS is achieved at R2=0.93 while RMSE=3.78 ton/ha. Therefore, there is no significant difference found by t-test for DBH, tree height, and AGB estimated from field-measured biometric, TLS and UAV data. The study reveals that the measurement of UAV and TLS for estimating aboveground biomass and carbon stock is very close in the mangrove forest. The application of TLS is comparatively difficult in mangrove forests due to its challenging environment. Therefore, as a low-cost technology, UAV can be used to estimate aboveground biomass and carbon stock accurately especially in the mangrove forest. Consequently, as a remote sensing technique, UAV can be used broadly in any inaccessible area of mangrove forest for estimating aboveground biomass and carbon stock towards the implementation of MRV under REDD+ initiatives.

For a long prior time, planning is being deprived of resulting unplanned urban growth that happen consequences the urban problems. A GIS-based site suitability analysis using the AHP model is performed with criterion: land use, population distribution, water network, drainage network and road network. The suitable growth sites are determined through expert opinion, pair-wise comparison matrix and finally determining the weighted value. This paper found out the potential urban growth mainly in ward no. 2, 7, and 6. Optimally suitable places are those sites where future urban development can easily occur and have all the required facilities with available commercial, industrial, and official land use, moderate and highly suitable places need some facilities e.g., water supply, drainage management, road network and rearrangement of land use. Very few and partly suitable sites need major involvement of facilities and revisions of present land use for potential urban development. This information can be useful for policy makers for planning processes as an acceptable scientific process for site suitability analysis in the municipality area for avoiding the urban problems and ensuring sustainable development

Urban green spaces are the indispensable component in city landscaping for realising a healthy living environment (HLE). The environmental quality was assessed in the Dhaka City Corporation (DCC) area, Bangladesh, by means of the existing green spaces, population density and air-quality mapping. This study revealed that Uttara, Mirpur 10, Kazipara, Darussalam, Shukrabad, Razabazar and the old city of Dhaka are the most significant environmentally critical areas. Also, it revealed that only six wards out of 92 wards of the DCC area (within the administrative boundary) met the per capita green spaces as per the standards of the World Health Organization (9 m2 per person) and the rest of the 86 wards required improvement of green areas. A green space plan map was also generated, which will be able to direct strategic options of the city's land-use planning to ensure an HLE. Information technology will provide valuable information about the management and implementation of new greenery development projects by DCC, Rajdhani Unnayan Karthipakaha and other voluntary organisation.

This book encourages children to maintain park etiquette (to show respect towards nature)