XXII ISPRS Congress 2012: Technical Commission VII

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Persistent identifier:: 1663813779

Title:: XXII ISPRS Congress 2012

Sub title:: Melbourne, Australia, 25 August-1 September 2012

Year of publication:: 2013

Place of publication:: Red Hook, NY

Publisher of the original:: Curran Associates, Inc.

Identifier (digital):: 1663813779

Language:: English

Additional Notes:: Kongress-Thema: Imaging a sustainable future

Corporations:: International Society for Photogrammetry and Remote Sensing, Congress, 22., 2012, Melbourne; International Society for Photogrammetry and Remote Sensing

Adapter:: International Society for Photogrammetry and Remote Sensing, Congress, 22., 2012, Melbourne; International Society for Photogrammetry and Remote Sensing

Founder of work:: International Society for Photogrammetry and Remote Sensing, Congress, 22., 2012, Melbourne; International Society for Photogrammetry and Remote Sensing

Other corporate:: International Society for Photogrammetry and Remote Sensing, Congress, 22., 2012, Melbourne; International Society for Photogrammetry and Remote Sensing

Document type:: Multivolume work

Volume

Persistent identifier:: 1663821976

Title:: Technical Commission VII

Scope:: 546 Seiten

Year of publication:: 2013

Place of publication:: Red Hook, NY

Publisher of the original:: Curran Associates, Inc.

Identifier (digital):: 1663821976

Illustration:: Illustrationen, Diagramme

Signature of the source:: ZS 312(39,B7)

Language:: English

Additional Notes:: Erscheinungsdatum des Originals ist ermittelt.; Literaturangaben

Usage licence:: Attribution 4.0 International (CC BY 4.0)

Corporations:: International Society for Photogrammetry and Remote Sensing, Congress, 22., 2012, Melbourne; International Society for Photogrammetry and Remote Sensing

Adapter:: International Society for Photogrammetry and Remote Sensing, Congress, 22., 2012, Melbourne; International Society for Photogrammetry and Remote Sensing

Founder of work:: International Society for Photogrammetry and Remote Sensing, Congress, 22., 2012, Melbourne; International Society for Photogrammetry and Remote Sensing

Other corporate:: International Society for Photogrammetry and Remote Sensing, Congress, 22., 2012, Melbourne; International Society for Photogrammetry and Remote Sensing

Publisher of the digital copy:: Technische Informationsbibliothek Hannover

Place of publication of the digital copy:: Hannover

Year of publication of the original:: 2019

Document type:: Volume

Collection:: Earth sciences

Chapter

Title:: [VII/4: METHODS FOR LAND COVER CLASSIFICATION]

Document type:: Multivolume work

Structure type:: Chapter

Chapter

Title:: MODELING SPATIAL DISTRIBUTION OF A RARE AND ENDANGERED PLANT SPECIES (Brainea insignis) IN CENTRAL TAIWAN Wen-Chiao Wang, Nan-Jang Lo, Wei-I Chang, Kai-Yi Huang

Document type:: Multivolume work

Structure type:: Chapter

terms of accuracy and implementation efficiency and determined the optimum for predicting the habitat of a rare plant. The predictive outcome from SDM would be used to prioritize field-survey areas for collecting fine resolution microclimatic, edaphic or biotic data for refining predictions of potential habitat in the later rounds of SDM or search areas for new population discovery. 2. STUDY AREA The study area consists of two parts, one part is Huisun Experimental Forest Station (HEFS), and the other is Tong-Mao Mountain, as shown in Figure 1. HEFS is in central Taiwan, and situated within 242°-24°5" N latitude and 1213-121 7' E longitude. This station is the property of Chung-Hsing University, and has a total area of 7, 477 ha. This station ranges in elevation from 454 m to 3, 419 m, and its climate is temperate and humid. Hence, this area has nourished about 1,100 plant species and is a representative forest in central Taiwan. This study took the samples from Sihwufongshan (Pine-breeze Mountain), Duhchuanling (Cuckoo Ridge) and Kuandaushan (Big-knife Mountain) trail in Huisun, Sihwufongshan elevation from 680 m to 840 m, the highest elevation of Duhchuanling approximately 810 m, and Kuandaushan elevation approximately 760 m. According to the climate record of this study area, the annual mean temperature is 21.0°C ; the monthly mean temperature highest is 30.6C in July, lowest is 20.5'Cin January; mean annual precipitation 2453.5 mm, the average relative humidity is 85%. Tong-Mao Mountain is situated at geographic coordinate 24°11'N latitude and 120°57' E longitude, near the Ta-chia River and Tong-Mao River, 10 km farther north from Huisun area. The elevation of Tong-Mao Mountain rises to 1690 m above sea level. According to the climate record of forest district office website, the annual mean temperature is 22.6°C ; mean temperature highest is 29°C in July, lowest is 15°C in January; mean annual precipitation 2580 mm. The mountain has rich ecological resources cycad-fern (CF), Blechnaceae family, is only found in mountains in central Taiwan, such as Huisun and Tong-Mao Mountain areas, and Huisun is the main habitat. Because of its limited ecological range, cycad-fern has been categorized as one of the rare, endangered species (Lu et al, 1986). A S... Tings ice mam s bx RS A Iora-Mao Mewtau = t hc i MN, 3: Jj > PE eRe LN Aha dz! Huisun Area ; j NS 2 $c: Sion = e fo nf } = Ye gl € di M € al m ® cycad-fern Streams + Mt. Paak [Station Area “8 tatometers International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, Volume XXXIX-B7, 2012 XXII ISPRS Congress, 25 August — 01 September 2012, Melbourne, Australia Figure 1 Location map of the study area. 3. MATERIALS AND METHODS 3.1 Data Collection We collected digital elevation model (DEM) with grid size 5 x 5 m, orthophoto base maps (1:10,000), and nine-date SPOT images (SPOT Image Copyright 2004 and 2005, CNES). In situ data (cycad-fern samples) were also acquired by using a GPS linked with an expandable antenna rod of 5m in length and a laser range finder, the error was usually below one meter after post-processing differential correction. Two-date SPOT images (07/10/2004 and 11/11/2005) were chosen because they have the best quality with the least amount of clouds among the nine-date SPOT images. 3.2 Data Processing Slope and aspect data layers were generated from 5 x 5 m DEM. The ridges and valleys in the study area were used together with DEM to generate terrain position layer. The main ridges and valleys were directly interpreted from the contour lines shown on the orthophoto base maps; these lines were then digitized to establish the data layer by using ARC/INFO software for later use. The relative position (Pj) of the test cell in the terrain is expressed as follows: Pj PV/ (PV * PR) (1) PV = Euclidean distance from P to the nearest valley line. PR = Euclidean distance from P to the nearest ridge line. P; = 0.0, terrain position is assigned to be "valley". P; = 1.0 , terrain position is assigned to be "ridge". The data layer in a vector format was converted into a new data layer in a raster format by ERDAS Imagine software, and then combined with DEM to generate terrain position layer (Skidmore, 1990). Vegetation indices were derived from the two-date SPOT-5 images, one in autumn, the other in summer, by using Spatial Modeler of ERDAS Imagine. CF samples obtained by GPS were converted into ArcView shapefile format for later use. There were 221 CF samples collected from Sihwufongshan, Duhchuanling and Kuandaushan-trail in Huisun forest station and one site at Tong-Mao Mountain by GPS in this study, but a part of these samples remained after data integration because some cycad-ferns fall within the same pixels with others, respectively. Five sampling schemes (SS), from SS-1 to SS-5, were created with different combinations of cycad-fern samples collected from the four sites. (A) SS-1, use two-thirds (2/3) of Sihwufongshan and Duhchuanling dataset for base model construction and the remaining (1/3) for model validation (evaluation). (B) SS-2, use the same base model built in SS-1 and only use independent samples taken from Kuandaushan-trail for base model evaluation. (C) SS-3, merge the samples from three sites in Huisun and then separate the dataset into two subsets, subset-1 containing two-thirds of the dataset for first data-merged model construction and subset-2 containing the remaining (1/3) for model evaluation. (D) SS-4, use the first data-merged model built in SS-3 and only use independent samples from Tong-Mao Mountain for model evaluation. (E) SS-5, merge aforementioned four-site samples and separate the dataset into two subsets, the first subset containing two-thirds of the dataset for the second

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